AI SYSTEMS ENGINEER Agentic AI, Multi-Agent Systems & Secure AI Workflows (U.S.) Remote • United States We're building production AI systems designed for enterprise environments. We're looking for exceptional AI systems engineers who enjoy solving difficult systems problems – not just writing code. Our work sits at the intersection of agentic AI, software architecture, enterprise systems, governance, security, and operational intelligence. We design AI systems that improve how organizations operate while meeting the standards required for production deployment. We value engineers who think in systems, challenge assumptions, and care deeply about building technology that is reliable, understandable, secure, and useful. If you're motivated by difficult engineering problems, thoughtful architecture, and building production AI systems for enterprise organizations, we'd like to hear from you. WHAT YOU'LL HELP BUILD Examples of the types of systems we design include: - Multi-agent AI systems - Enterprise AI assistants - Secure AI workflows - Enterprise workflow automation - AI-powered knowledge systems - Human-in-the-loop decision support - Document intelligence - Retrieval-Augmented Generation (RAG) - AI memory and retrieval systems - AI evaluation and testing frameworks - Secure enterprise AI platforms - AI governance capabilities - Operational intelligence platforms TECHNICAL EXPERIENCE WE VALUE We're interested in engineers with experience in some combination of: - Python - AI Agent Development - LangGraph - LangChain - Large Language Models - API Development - Vector Databases - Software Architecture - Enterprise Systems Integration - Information Security Experience with OpenAI, Anthropic, Model Context Protocol (MCP), cloud infrastructure, workflow orchestration, observability, distributed systems, or regulated technology environments is also valuable. We do not expect expertise in every technology. We care far more about engineering judgment, systems thinking, demonstrated execution, and continuous learning than checking every technology box. THE PROBLEMS WE ENJOY SOLVING The engineers who thrive here enjoy questions like: - How should multiple AI agents coordinate work? - How should humans remain in control of important decisions? - How should production AI systems scale safely? - How should memory be designed for enterprise AI? - How should AI systems balance operational performance with governance, security, and reliability? - How should AI systems create measurable business value? If those questions excite you, you'll probably enjoy working with us. WHAT MAKES SOMEONE SUCCESSFUL HERE We're looking for engineers who: - Think in systems rather than individual features. - Care deeply about production quality. - Enjoy solving ambiguous technical problems. - Communicate complex ideas clearly. - Balance speed with sound engineering judgment. - Build practical solutions rather than chasing hype. - Continuously learn, experiment, and improve. We're significantly more interested in systems you've built than technologies you've used. Please provide specific examples that demonstrate your role, engineering decisions, and measurable outcomes. We recognize that many engineers use AI as part of their workflow. You're welcome to do the same. However, your application should accurately reflect your own experience, judgment, and technical thinking. We respect the confidentiality of your current and former employers, clients, and partners. Please do not include proprietary or confidential information in your application. Describe your work at a level that demonstrates your engineering approach without disclosing protected information. PROFESSIONAL STANDARDS We value integrity, sound engineering judgment, and respect for intellectual property. Please do not include confidential, proprietary, export-controlled, or other non-public information belonging to your current or former employers, clients, or partners in your application or work samples. We're interested in your engineering approach, architectural thinking, and problem-solving methodology – not protected information belonging to others. If you share code, architecture diagrams, technical documentation, or project examples, please ensure you have the legal right to do so and identify any material open-source or third-party technologies where appropriate. By submitting application materials, you represent that you have the legal right to share them and that doing so does not violate any confidentiality, intellectual property, employment, consulting, or other contractual obligations. Any engagement, if offered, will be subject to a separate written agreement covering confidentiality, intellectual property ownership, compensation, and other applicable terms. Submission of an application or participation in the evaluation process does not create any employment, independent contractor, partnership, joint venture, agency, fiduciary, or other business relationship with 26ers AI, nor does it obligate either party to enter into any future engagement. 26ers AI reserves the right to evaluate applications, discontinue discussions, modify the hiring process, or decline to pursue any engagement at its discretion. Nothing in this posting should be construed as an offer of employment or an offer to contract.

The AI Process Optimization Specialist is responsible for evaluating, designing, implementing, and continuously improving business processes through the strategic use of Artificial Intelligence (AI), automation, and digital technologies. This role works across all departments to identify inefficiencies, recommend AI-driven solutions, develop implementation plans, and ensure employees successfully adopt new technologies. The ideal candidate combines business analysis, process improvement, project management, and AI expertise to help the organization become more efficient, scalable, and competitive. Key Responsibilities Business Process Analysis Analyze existing business workflows across all departments. Document current processes and identify bottlenecks, redundancies, and manual tasks. Interview department leaders and staff to understand operational challenges. Create workflow diagrams and process documentation. AI Opportunity Assessment Identify tasks that can be automated or enhanced using AI. Evaluate emerging AI technologies and recommend practical business applications. Research AI platforms, software, and automation tools. Conduct cost-benefit analyses for proposed AI initiatives. Workflow Optimization Design more efficient workflows using AI-assisted processes. Develop standardized operating procedures (SOPs). Reduce repetitive manual work. Improve communication and collaboration between departments. Create scalable systems that grow with the business. AI Implementation Configure and deploy AI tools and automation platforms. Coordinate integrations between business software. Test workflows before deployment. Troubleshoot implementation issues. Measure effectiveness using key performance indicators (KPIs). Employee Training & Change Management Train employees on new AI tools and workflows. Develop documentation, tutorials, and training materials. Promote AI adoption throughout the organization. Gather user feedback and continuously improve processes. Performance Monitoring Track productivity improvements and ROI. Measure time savings and operational efficiencies. Maintain dashboards and performance reports. Recommend additional optimization opportunities. Innovation & Continuous Improvement Stay current with advancements in Artificial Intelligence. Evaluate new AI platforms and emerging technologies. Pilot new automation initiatives. Recommend long-term AI strategies that align with company goals. Preferred Qualifications Bachelor's degree in Business, Information Systems, Computer Science, Engineering, or related field (or equivalent experience). Experience in business process improvement or operations management. Strong understanding of AI technologies and automation platforms. Experience with workflow automation tools (Zapier, Make, n8n, Microsoft Power Automate, etc.). Familiarity with Large Language Models (LLMs) such as ChatGPT, Claude, Gemini, and Microsoft Copilot. Excellent analytical and problem-solving skills. Strong project management abilities. Outstanding written and verbal communication skills. Ability to work independently and lead cross-functional initiatives. Technical Skills Preferred experience with: Artificial Intelligence platforms Workflow automation tools CRM systems Project management software Documentation platforms Data analytics and reporting tools API integrations Microsoft 365 and Google Workspace Low-code/no-code automation platforms Core Competencies Strategic Thinking Process Improvement Critical Thinking Systems Analysis Project Management Change Management Business Communication Continuous Learning Innovation Leadership Organization Collaboration Success Metrics Performance will be measured by: Reduction in manual labor hours Increased operational efficiency AI adoption across departments Employee productivity improvements Workflow automation rate Cost savings generated Return on AI investments (ROI) Employee satisfaction with new systems Process documentation completeness Successful delivery of optimization projects Typical Projects An AI Process Optimization Specialist may: Build AI assistants for customer service and internal support. Automate repetitive administrative tasks. Develop AI-powered knowledge bases. Optimize project management workflows. Improve sales and marketing processes using AI. Streamline onboarding and employee training. Create automated reporting dashboards. Integrate AI into website development, customer support, accounting, HR, and operations. Develop company-wide AI usage standards and best practices. Mission To transform the organization into a highly efficient, AI-enabled business by continually identifying opportunities to automate work, improve processes, reduce costs, enhance decision-making, and empower employees through the effective use of Artificial Intelligence.

Description We are a US-based software company that already runs AI coding agents in daily engineering work. We are looking for a senior agentic development expert to help us push further. This is a specialist engagement, not an entry-level or generalist AI role. We want someone who has done this for real teams shipping production code and can go deep quickly. The engagement starts with a focused review of how we use agents today and where they can safely take on more, followed by a practical plan we can act on. Specifics are shared under NDA once we shortlist. You are a strong fit if you: - Have designed and rolled out agentic development workflows for a production engineering team, with results you can point to - Know Claude Code at an expert level: harness setup, context management, custom skills and slash commands, subagents, hooks, and MCP - Have integrated agents into an existing codebase and CI, including automated review and guardrails - Can advise on running agents securely around proprietary code and secrets - Can assess a team's current setup and turn it into concrete, sequenced steps This is probably not the right fit if: - Your experience is mostly personal projects, tutorials, or casual use of AI chat tools - You have used AI coding tools but have not set up team-level workflows or guardrails - You are a generalist looking to branch into AI Nice to have: - Python backend and web application experience - Experience with automated, agent-driven code review and test workflows Engagement: - Remote, expert-level rate - Short initial engagement with potential to extend - Some availability for scheduled, recorded calls - NDA required before we share specifics To apply (proposals without these will not be considered): - A specific example of an agentic development setup you built for a team, what you designed, and the outcome - The AI coding agents you have worked with and the depth of that work - Links to anything that shows your work (skills or agent configs, writeups, repos, demos), if you can share them

We are seeking an experienced AI workflow / operations consultant to help us build repeatable “business of the future” blueprints for niche service industries. We are not building a new AI product. We want help identifying the best existing tools, workflows, and automation opportunities to modernize service businesses in a practical, scalable way. We want someone who can help us: map current workflows identify the best opportunities for AI and automation recommend the right tool stack define what should stay human vs. what should be automated create standardized implementation blueprints we can deploy across multiple clients We are looking for someone with real operational depth, not just generic AI enthusiasm. Bonus if you have worked in: healthcare legal compliance-sensitive service businesses CRM / automation / intake / communication systems Please send examples of similar work and explain how you would approach building a scalable modernization blueprint for these kinds of businesses.

We operate a production AI/LLM auditing platform used by a large enterprise client. This platform transcribes recordings of in-store visits completed by field representatives, then runs an LLM-driven audit schema against those transcripts to score whether specific criteria were met. The platform is live and delivering value. We're now investing in a dedicated AI specialist to push accuracy higher, expand the feature set, and bring deeper expertise to how we evaluate and iterate on our LLM pipeline. What you'll do - Build out our evaluation loop. We currently test our audit schema weekly. We want to move to more frequent, more granular testing, the full schema or individual audit questions, on demand. - Improve scoring accuracy. Our benchmark is 90%+ accuracy on most audit questions. You'll drive us there, identify the questions where 90% isn't realistic and explain why, and push a defined subset of high-priority questions well beyond 90%. - Assess the approach itself. Determine whether we need new audit schemas and questions, or whether the current approach should be refactored for better accuracy and capability. We want your judgment here, not just execution. - Ship new capabilities. -- Keyword search over transcript text, with Boolean operators, phrase search, and grouping. Returns matching snippets plus a count of transcripts containing the term. Transcripts are ASR output and imperfect, so the design needs to account for that. -- Sentiment analysis: merchant sentiment and agent sentiment across a transcript (negative / neutral / positive), plus detection of sentiment shift over the course of a conversation (e.g., a merchant who started negative and ended positive). - Evaluate emerging tooling and make recommendations we can act on. - Potentially build a schema management UI so our non-developer team can modify audit questions without engineering involvement. - Communicate frequently. We want regular written progress recaps, not silence between milestones. What we're looking for - Strong hands-on experience building and shipping LLM-powered systems in production, not just prototypes - Real depth in LLM evaluation: building eval sets, measuring accuracy against ground truth, regression testing prompts and schemas, and reasoning about where models fail and why - Prompt engineering and structured-output experience (classification, scoring, extraction) - Experience working with ASR/transcript data and its failure modes is a strong plus - Comfort with search implementation (Boolean query parsing, full-text search) is a plus - Sentiment analysis experience beyond off-the-shelf APIs - Ability to form an opinion, defend it, and communicate it clearly in writing to both technical and business stakeholders - Self-directed — you'll be trusted to identify the right problems, not just close tickets Nice to have - Experience with RAG, fine-tuning, or model selection tradeoffs at scale - Frontend capability sufficient to build an internal admin/config UI - Background in compliance, QA, or audit-adjacent domains To apply Please include: - A brief description of an LLM system you took from prototype to production, and specifically how you measured and improved its accuracy. - Your approach to building an evaluation harness for a scoring/classification task where ground truth is human-labeled. - Your availability and hourly rate. Applications that appear to be generic or AI-generated without substance will not be considered. Please reference the word "transcript" in your first sentence so we know you read this.

We are looking for a highly capable AI consultant with a strong technical background in software development, AI-assisted workflows, and research. The ideal candidate is someone who understands modern AI tools, can quickly evaluate information for accuracy, and can help accelerate development, documentation, and decision-making across a variety of projects. * Utilize AI tools such as Claude, ChatGPT, and other leading platforms to support research, analysis, and development * Verify information, identify reliable sources, and distinguish between speculation and fact * Assist with software development, debugging, and technical problem-solving * Build scripts, automations, prototypes, and internal tools as needed * Help organize complex information and knowledge systems, including work within Obsidian * Translate ideas and concepts into actionable plans, technical documentation, and working solutions * Collaborate on a wide range of technical, operational, and strategic projects Qualifications * Strong software development experience * Proficiency with modern programming languages such as Python, JavaScript/TypeScript, or similar * Extensive experience using AI tools, including Claude, ChatGPT, Cursor, and related technologies * Ability to critically evaluate information and conduct high-quality research * Strong understanding of AI concepts, terminology, and emerging technologies * Excellent written and verbal communication skills * Comfortable working independently and navigating ambiguity

We're seeking a skilled Full Stack Developer to join our team. You'll debug and resolve errors within our applications, support improvements, troubleshoot issues, and integrate our apps with our CRM system. Just as important: you'll help keep our GHL-based AI agent and voice AI systems running smoothly for live clients. Read the whole post before applying. We've written it to be direct on purpose. If any of it doesn't sound like you, that's okay , please self-select out. We'd rather know now. What we're looking for We need a contributor, not just a doer. That means someone who takes initiative, spots issues before they become problems for the client, and drives toward solutions instead of waiting to be told what to do next. If you're the type who finds the answer rather than asking us for it, you'll do well here. If you need your hand held on every step, this isn't the right fit. We work with live clients on voice AI and AI agents, so being proactive and responsive is not optional. When something breaks or drifts, we need you evaluating, fixing, and improving it, thinking forward about the end-user experience, not just reacting after a client complains. Responsibilities • Debug and provide solutions for errors in web and mobile applications.. • Support ongoing improvements and optimizations.. • Troubleshoot technical issues efficiently, ideally before they reach the client.. • Integrate applications with our CRM system (GoHighLevel / GHL) for seamless functionality.. • Connect systems and third-party services via APIs to enhance platform capabilities.. • Support, adjust, and maintain GHL AI agents and voice AI workflows so they perform reliably for clients.. Requirements • Proven experience as a Full Stack Developer.. • Strong proficiency in front-end and back-end technologies (e.g., JavaScript, React, Node.js, Python, etc.).. • Experience with GHL CRM integrations.. • Working knowledge of and comfort with GHL AI agents and automations — you don't need to be a specialist, but you should be able to get in, understand how they're built, make adjustments, and pick things up quickly.. • Familiarity with or genuine willingness to dig into voice AI. We expect everyone on the team to be able to work with it.. • Proficiency in designing and implementing REST-based API connections.. • Excellent problem-solving and debugging skills.. • Ability to work independently, take initiative, and meet deadlines.. How we work • We're engaging you — not your agency. The person we hire is the person doing the work. If you subcontract or hand work to others, this isn't a fit.. • Short leash, high trust. Everyone starts on a trial basis. We give people room to learn, but you'll need to learn fast, dive in, and prove it quickly. If you're trying to learn the fundamentals on the job, this role isn't for you.. • Own your outcomes. Bring the thinking, not just the hands. Recognize what the end user's experience will be and drive it.. If that sounds like the environment you want, we'd love to hear from you.

We are looking for a strong software engineer who can build practical automation systems using AI, APIs, and modern development tools. This role is for someone who can take messy business workflows, understand the goal, and build working systems that save time, reduce manual work, and improve execution. You should be comfortable building automations, integrating tools, working with APIs, writing clean code, and using AI tools like OpenAI, Claude, or similar models to create useful business applications. What You’ll Work On You will help build and improve systems such as: AI-powered research and data extraction workflows CRM and sales process automations Email, spreadsheet, and database automations Internal tools and dashboards API integrations between business software Web scraping and data enrichment workflows when appropriate AI agents or assistants that help with repetitive business tasks Automation around deal screening, reporting, lead research, and document creation Ideal Candidate We are looking for someone who is practical, fast, and can figure things out without needing step-by-step instructions. You should have experience with: Python and/or JavaScript APIs and webhooks OpenAI, Claude, or other LLM APIs Automation tools like Zapier, Make, n8n, Airtable, Google Sheets, HubSpot, Salesforce, or similar Databases such as PostgreSQL, Supabase, Firebase, or similar Basic front-end or internal tool development Web scraping, data cleaning, and structured data workflows GitHub and clean documentation What Matters Most We do not need someone who only talks about AI. We need someone who can actually build. The right person should be able to: Understand a business process quickly Recommend the simplest technical solution Build fast prototypes Turn prototypes into reliable workflows Communicate clearly Document what was built Improve systems over time Nice to Have Experience with any of the following is a plus: Private equity, M&A, finance, or investment workflows Deal sourcing or lead generation systems CRM automation Data enrichment tools AI research agents Browser automation Cloudflare, AWS, Google Cloud, or similar infrastructure Engagement This will start as a part-time project-based role, with the potential to become ongoing if the work is strong. Estimated workload: 5 to 15 hours per week to start. To Apply Please include: Examples of automations or AI tools you have built The tech stack you usually work with A brief explanation of how you would approach automating a messy manual workflow Your hourly rate Your availability Please do not send a generic application. If your response looks copied and pasted, it will be ignored.

We're hiring a senior AI developer to build and deploy AI solutions for a fintech/credit-union platform. The work spans autonomous banking agents, fraud detection, credit scoring, and bill-pay/invoice automation — at the intersection of LLMs, cloud infrastructure, and financial-domain expertise, with security and compliance built in from the start. This is a long-term, ongoing engagement. What you'll do: AI agents & orchestration - Design, build, and deploy multi-agent systems using Amazon Bedrock Agents, LangChain, and related frameworks - Architect agentic workflows for core banking use cases: credit scoring, fraud detection, bill-pay automation, invoice management - Define agent personas, memory strategies, tool-use patterns, and escalation paths for production banking agents LLM engineering - Fine-tune, prompt-engineer, and evaluate LLMs for financial-domain tasks - Build RAG pipelines over credit-union knowledge bases, policy docs, and member data - Implement guardrails, content filtering, and compliance checks for safe, regulated outputs - Monitor performance, hallucination rates, and latency against SLAs Cloud infrastructure (AWS & Azure) - Architect and manage AI/ML workloads on AWS (Bedrock, SageMaker, Lambda, S3, IAM, VPC) and Azure (OpenAI Service, Azure ML, AKS) - Design secure, cost-optimized environments compliant with NCUA, PCI-DSS, and SOC 2 - Implement infrastructure-as-code with Terraform or AWS CDK DevOps & MLOps - Build and maintain CI/CD pipelines (GitHub Actions, Jenkins, CodePipeline, Azure DevOps) - Containerize services with Docker, orchestrate with Kubernetes (EKS/AKS) - Apply MLOps best practices: model versioning, A/B testing, canary deployments, automated rollback - Stand up observability with logging, tracing, and alerting Python development - Write clean, well-tested Python for AI pipelines, REST APIs, and data workflows - Build FastAPI/Flask microservices exposing agent capabilities to frontend and core banking systems - Integrate with financial data sources, core banking APIs, and third-party fintech services Banking applications - Build credit-scoring models using alternative data and explainable AI (XAI) - Develop real-time fraud detection with behavioral analytics, anomaly detection, and auto-decisioning - Create conversational agents for bill pay, account management, and member self-service - Automate invoice workflows: extraction, classification, approval routing, reconciliation - Partner with compliance/risk to keep AI decisions auditable, fair, and regulatory-compliant What you should have: - 5+ years software engineering; 3+ years in AI/ML or LLM engineering - 2+ years building AI for banking, credit unions, or financial services - Hands-on experience with Amazon Bedrock, LangChain, Python, AWS, and infrastructure-as-code - Working knowledge of NCUA, PCI-DSS, SOC 2, GLBA, and Fair Lending requirements - Bachelor's or Master's in Computer Science, Software Engineering, Data Science, or related field Nice to have: - AWS or Azure AI/ML certifications - Open-source LLM experience (Llama, Mistral, Phi) and self-hosted inference (vLLM, Ollama) - Vector databases (Pinecone, OpenSearch, pgvector) - Graph-based fraud networks and graph ML - AI governance / responsible AI framework experience - Prior work at a credit union, community bank, or fintech lending platform To apply, please share: - Your resume highlighting AI and banking project experience - A brief note on your most impactful AI agent or LLM project in a financial-services context - Links to GitHub, portfolio, or published papers (optional but encouraged)

Role Overview You are the Executive AI Enablement Lead at AIVC, the person whose job is to make the executives at AIVC’s client businesses true power users of Claude, Cowork, and code- and agent-driven workflows. AIVC partners with operator businesses to drive AI-led EBITDA growth, and part of that work is bringing each company’s most senior leaders up the AI curve. You’re the person who personally designs and runs that path on every engagement: assessing where a given client executive is today; curating the right materials, videos, and course content; running 1:1 coaching; building executive playbooks; and acting as their daily operator-in-the-loop until the new workflows stick. The first concrete instance is already lined up, a named client managing partner has explicitly asked for the fastest path to becoming a power user of Claude, Cowork, and Claude Code / Skills. From there you scale: same treatment to additional client executives across the portfolio, then a documented set of executive-grade playbooks and patterns that compound across every future engagement. You are bias-toward-results – a win is the client executive’s calendar-week looking different, not a beautifully written rubric nobody uses. What You’ll Own (Outcomes) • Within 30 days of pairing with the first client managing partner, they have a working daily routine in Claude, Cowork, and Code/Skills that’s already replacing or improving how they handle at least three recurring tasks • Within the first quarter of the engagement, the client executive is a true power user — running multi-step workflows, custom Skills/Projects, and agent-assisted tasks without needing coaching scaffolding for the basics • A documented set of executive playbooks (research, writing, analysis, synthesis, workflow automation, agent-assisted tasks) that compound across every client engagement, not one-offs • A curated, current library of learning materials, videos, example workflows, and Claude-native patterns — including a clear point of view on which external courses, tutors, or expert resources are worth plugging in • Observable change in how client executive cohorts use AI: from reactive chat to repeatable, structured, outcome-oriented workflows • A foundation of training assets and patterns that scales beyond executive coaching into broader client teams in year two • A reputation among AIVC’s clients as the trusted go-to for “how do I do this better in Claude” — measured by inbound demand and engagement expansion What You’ll Do (Responsibilities) • In the first weeks: build the first client managing partner’s tailored upskilling plan — assess current usage, identify the highest-leverage workflows for their day-to-day, curate the right mix of materials / videos / course content, and recommend any tutor or expert-guided support to fold in • Provide 1:1 coaching for client executives — managing partners, founders, C-suite leaders — on Claude, Cowork, and code- and agent-based workflows • Design tailored training plans per executive that go beyond basic onboarding into advanced usage, with explicit progression from chat → workflows → agents • Curate the best external materials (videos, courses, blog posts, example projects) and rewrap them into client-ready, AIVC-flavored learning paths • Teach practical, high-leverage use cases live: research, writing, analysis, synthesis, workflow automation, and agent-assisted tasks • Help client executives move from general chat usage into repeatable workflows — Claude Projects, Skills, scheduled Cowork tasks, MCP integrations, custom agents • Serve as a real-time tutor and expert resource for client executives — over Slack, in meetings, on-site, and in async written feedback • Run office hours, workshops, and informal Q&A sessions inside client teams to keep adoption sticky between coaching sessions What We’re Looking For (Required) • Deep hands-on expertise with Claude across every surface (Claude.ai, Claude Projects, Claude Code, Claude Skills, Claude API) — and an active habit of pushing the edges of each • Strong working fluency with Claude Cowork specifically, including scheduled tasks, connected apps / MCPs, and the broader workflow surface • Strong capability with code-enabled AI workflows: you can write Python and/or TypeScript, build agents, configure MCP integrations, and ship a working internal automation end-to-end without needing an engineer • Demonstrated ability to teach non-technical but highly demanding users — you’ve made executives, founders, or senior operators meaningfully better at something complicated, not just trained engineers • Strong workflow design instinct — you can translate messy business questions into clean prompts, workflows, and systems • Polished, discreet, and effective in high-touch client executive settings — high EQ, low ego, comfortable representing AIVC inside senior client environments and around senior decision-makers • Strong bias toward practical results over theoretical AI knowledge — the metric is the client executive’s behavior change, not the elegance of the explanation • Excellent written and verbal communication; you can write a playbook a client executive will actually read and use • Comfort with significant travel to client sites and embedded, on-site engagement work • 5+ years of professional experience across some mix of: applied AI / ML, technical training and enablement, developer relations, solutions engineering, executive coaching, management consulting, or chief of staff / senior operator roles to executives Helpful If You Have (Preferred) • Prior experience coaching or supporting C-level executives, founders, or managing partners as a client-facing professional — executive coach, principal solutions engineer to executive customers, chief of staff to a CXO, or partner-level consultant • Background that combines technical depth with people skills — developer relations, solutions engineering, technical training, or learning & development at a frontier AI or developer-tools company • Direct experience building executive-facing training programs or curricula that demonstrably moved adoption inside other organizations • Hands-on familiarity with the Anthropic product surface specifically: Claude Projects, Claude Skills, Claude Code, MCP server development, Claude API • Track record of getting non-technical users to genuinely adopt a technical tool — i.e., users who chose to keep using it after the training ended • Background in management consulting, professional services, executive coaching, or learning & development — especially in environments where the customer was a senior external client • An active personal portfolio of AI work (workflows, automations, blog posts, talks, open-source contributions) you can point to • Comfort building light tooling (a Notion playbook system, a Claude Skills catalog, a small dashboard) without needing engineering support • Familiarity with AIVC’s model — operator business engagements, EBITDA-led measurement, and the broader compounding intelligence layer — or eagerness to come up the curve quickly