We are looking for a hands-on Forward Deployed AI Engineer to help build practical AI systems This is not a pure backend role and not a strategy-only consulting role. You will work close to end users, understand how their workflows actually operate, and then build AI-enabled tools that solve specific business problems. The ideal person is a strong software engineer who is comfortable with ambiguity, can communicate clearly with non-technical stakeholders, and can take an AI prototype from idea to something reliable and usable. What you will do - Learn the business workflows, systems, data, and constraints. - Build AI applications using Claude or similar large language models. - Use the right mix of prompting, retrieval, tool use, agents, and workflow automation. - Own delivery from scoping through prototype, testing, hardening, and handoff. - Create evaluations to determine whether the system is accurate, reliable, and safe enough to use. - Translate between domain experts and technical implementation. - Work carefully with sensitive or regulated data. - Document what you build so it can be maintained and reused. What we are looking for - Strong Python engineering skills. - Hands-on experience building with LLMs, preferably Claude or the Anthropic API. - Experience with RAG, structured prompting, tool use, evaluation, or agentic workflows. - Ability to operate independently in a messy, ambiguous environment. - Strong communication skills with both technical and non-technical stakeholders. - Track record of shipping working software, not just demos. - Comfort working with real-world data, integrations, and imperfect requirements. Helpful but not required - Prior forward deployed engineering, solutions engineering, or technical consulting experience. - Experience building AI tools for enterprise customers. - Experience in regulated or sensitive-data environments. - Familiarity with validation, auditability, traceability, or compliance-oriented workflows.

26ers is building Human + AI operating systems that help organizations improve decision quality, execution speed, and organizational leverage. We are seeking a customer-facing AI Architect who can work directly with executives, operational leaders, and technical teams to design practical AI solutions that solve real business problems. This role helps organizations identify high-value AI opportunities, redesign workflows, modernize operations, and implement Human + AI operating systems that improve execution, decision-making, and organizational effectiveness. The ideal candidate can move fluidly between customer conversations, workflow discovery, solution design, governance considerations, and implementation planning. Responsibilities • Participate in customer discovery and solution design conversations • Analyze current-state workflows and identify AI transformation opportunities • Design Human + AI operating models, agentic workflows, and operational systems that improve execution and decision-making • Create solution blueprints, implementation plans, and statements of work • Collaborate with implementation developers and technical delivery teams • Consider data governance, security, compliance, and operational requirements throughout solution design • Contribute to the development of reusable 26ers methodologies, frameworks, and institutional knowledge • Design systems that capture, structure, and operationalize organizational knowledge and institutional learning Ideal Experience • Experience designing AI-powered business workflows and operational systems • Strong understanding of OpenAI, Claude, and modern LLM-based solution design • Experience with workflow orchestration platforms, AI agents, automation systems, and API-based architectures • Strong understanding of data governance, information security, and enterprise AI deployment considerations • Experience translating business requirements into solution architectures, implementation plans, and statements of work • Customer-facing experience in consulting, solution engineering, professional services, digital transformation, or technical advisory roles • Experience conducting discovery workshops, workflow assessments, and current-state/future-state design exercises • Understanding of operating model design, workflow modernization, and organizational transformation • Strong written and verbal communication skills with executive stakeholders • Ability to leverage AI tools to rapidly produce architecture drafts, blueprints, requirements documents, implementation plans, training materials, and customer deliverables Nice to Have • Experience with Gemini, MCP, LangGraph, CrewAI, AutoGen, or similar orchestration frameworks • Experience with n8n, Make, Zapier, or workflow automation platforms • Experience with vector databases, RAG architectures, and organizational knowledge systems • Experience building or deploying multi-agent systems • Government, healthcare, financial services, or other regulated industry experience • Startup, founder, or early-stage company experience • Experience designing systems that capture institutional knowledge, operational learning, or organizational intelligence • Military, consulting, enterprise software, or transformation leadership experience Success in this role • Quickly understand a client's operating environment, workflows, and business objectives • Identify high-value opportunities for AI-enabled transformation and operational leverage • Translate customer goals into practical solution designs, implementation plans, and delivery roadmaps • Balance innovation, governance, security, and operational realities • Help organizations move from AI experimentation to operational execution This role may begin on a contract basis and expand into a longer-term strategic partnership as 26ers grows.

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

We are a small residential real estate investment company seeking an AI Solutions Architect to enhance our acquisition platform. The role involves designing and implementing AI solutions to improve data analysis and decision-making processes. The ideal candidate will have experience in AI architecture and a strong understanding of real estate data analysis.

We're hiring 2 experienced developers to build AIOS deployments for our growing client base. FluentOS is a 9-person team that builds AIOS (AI operating systems) that connect a business's existing platforms together and run AI agents on top of them. We're onboarding 6–7 new client projects every week and need two more builders who can take a project and deliver it. The industries we work in: We deploy across a wide range of professional and service businesses, so you'll get variety: - Financial services & wealth advisory - Tax & accounting firms - Dental and medical practices - Home services & roofing - Property management Each client runs on a different stack — CRMs, comms tools, scheduling, payment systems, document and data sources — and our job is to unify those into one system and build agents that operate across them (lead response, follow-up, reporting, document workflows, estimating, intake, and more). What you'd be building: - AIOS deployments end to end — integrating client platforms via their APIs - AI agents that read/write across those connected systems - Reliable, production-grade automations that real businesses depend on daily What we're looking for: - Proven delivery experience — you've shipped projects clients actually use, not just personal experiments - Strong coding background (Python and/or TypeScript); comfortable with API integrations and agent frameworks - Experience with LLM/agent development (Anthropic/Claude, tool use, multi-step agents) is a big plus - Fast, organized, and communicative — we move quickly and build as a team, not in isolation - Able to work closely with Ray, our lead developer, who'll get you ramped into live projects The setup: - 1099 contract, paid per project — not salaried - Steady, scalable volume (6–7 new projects/week) means consistent work for builders who deliver - Strong potential for ongoing, long-term collaboration as we scale To apply: Tell us briefly about a real project you've built and delivered — ideally something involving API integrations, automation, or AI agents. Include links to work or repos if you have them. Please start your reply with the word "FLUENT" so we know you read this. We'll be scheduling interviews shortly.

Looking for an elite problem solver, either an ex-MBB consultant with deep technical fluency or a seasoned AI Product Manager, to act as the crucial bridge between business operations and technical AI implementation. You will be responsible for dissecting client operations, prototyping the AI logic, writing flawless engineering briefs, and driving the development team to the finish line. What You Will Do: Workflow Audits & Discovery: Lead deep-dive discovery sessions. Map out existing operational workflows, identify bottlenecks, and pinpoint high-ROI opportunities for AI automation. Prototyping & Technical Translation: Because you are an AI power user, you will prototype the initial AI prompts and logic. You will then translate your operational findings into crystal-clear engineering briefs (or PRDs) so developers know exactly what to build. Development Management: Act as the project lead during execution. Manage the engineering workstream, clear roadblocks, and ensure the final solution is delivered on time, within budget, and achieves the strategic goal. Stakeholder Alignment: Act as the primary liaison between non-technical business leaders and the technical development team. Requirements & Qualifications: Top-Tier Pedigree: 1+ years of experience at a top management consulting firm (MBB, Big 4, Tier 2) OR proven experience as a Technical/AI Product Manager. Advanced AI Fluency: You are an AI power user. You possess advanced prompt engineering skills (e.g., chain-of-thought, few-shot) and know how to force LLMs to output reliable, structured data. Elite Structured Thinking: You excel at turning highly ambiguous, messy business processes into clean, logical frameworks (using Lucidchart, Miro, etc.) and comprehensive technical requirements. Project Leadership: Proven track record of managing technical resources, tracking deliverables, managing budgets, and driving teams to a deadline.

Guardian Senior Solutions GoHighLevel + Retell AI Build — Job Posting & Scope of Work Posted by: Paul · Guardian Senior Solutions (GSS) Orange County, California — remote contractor accepted Project overview Guardian Senior Solutions (GSS) is a direct-to-consumer senior care navigation platform in Orange County, California. We are a conflict-free alternative to referral platforms like A Place for Mom — we coordinate care, legal, financial, and home equity needs for senior families rather than operating as a care provider ourselves. We need a GoHighLevel (GHL) build that automates our lead-to-appointment pipeline end to end: from the moment a lead comes in (web form, paid ad, social DM, referral) through AI-driven outreach (voice via Retell AI, SMS, email) to a booked assessment appointment with one of our case managers, by phone or in person. This is a real-time-sensitive use case — families reaching out are often in or near a care crisis, so speed and reliability of follow-up directly affects whether we can help them. What success looks like • A lead that fills out a form, comments on a social post, or calls in gets a response within 5 minutes, every time, with no silent failures. • Qualified leads are automatically routed into a clear pipeline and booked onto a case manager's calendar without manual intervention. • We can see, in one dashboard, exactly where every lead is and whether any have gone stale. • The system is documented well enough that we are not permanently dependent on the person who built it. Scope of work 1. Core GHL architecture • Build a 6-stage lead pipeline: New Lead → Contacted → Nurturing → Appointment Booked → Consultation Complete → Not Ready / Lost. • Configure custom fields: care urgency (1–5), who care is for (self / parent / spouse), homeowner Y/N, estimated home value, legal documents in place Y/N, lead source. • Set up lead source tagging across all channels: Google Ads, Meta Ads, organic/social, referral partner (by name), direct, and any purchased lead lists. • Build a reporting dashboard tracking: leads by source, speed-to-contact, appointment conversion rate, show rate, and pipeline value by stage. 2. Retell AI voice integration • Integrate Retell AI with GHL so that a new lead triggers an outbound AI voice call within 5 minutes of form submission. • Build fallback logic: if the call is not answered, automatically fall back to SMS rather than silently dropping the lead. • Configure the call outcome (answered / voicemail / booked / declined) to write back into the GHL contact record and move the pipeline stage accordingly. • Work with us to finalize the AI voice script and qualifying questions (we have a draft framework already). 3. Lead nurture automation • Build the speed-to-lead workflow: AI call + SMS on form submit, second call attempt at 1 hour, email at 2 hours, manual task created for a human follow-up at 24 hours if still unresponsive. • Build a 21-day nurture drip for leads not yet ready to book, mixing educational email content with SMS check-ins (content outline will be provided). • Build appointment confirmation and reminder sequences (instant confirmation, 24-hour reminder, 1-hour reminder) via email and SMS. • Build a post-consultation follow-up sequence including a same-day summary, a 3-day check-in, and a 7-day review request (conditional on a positive-outcome tag). 4. Social + email content engine • Set up GHL's Social Planner across Facebook, Instagram, LinkedIn, and TikTok with an approval workflow so content is AI-drafted but human-approved before publishing. • Set up a weekly email campaign workflow: AI-assisted draft, human approval step, then send. • Connect inbound engagement (Facebook/Instagram DMs and comments, web chat, SMS, email replies) to GHL Conversations and route qualified leads into the Conversation AI for qualification. • Flag clearly in writing if TikTok DM-to-CRM integration is not currently supported natively by GHL, and propose a workaround if one exists. 5. Appointment booking & case manager routing • Integrate calendar booking (Calendly or GHL's native calendar) so qualified leads can be booked directly onto the correct case manager's calendar, distinguishing between phone and in-person assessment appointment types. • Build routing logic if we have more than one case manager (e.g., by territory, availability, or caseload). 6. Reliability, testing, and handoff • Idempotency checks so a lead submitting twice, or a webhook firing twice, does not trigger duplicate calls or duplicate pipeline entries. • A staging/test mode so new or modified workflows are tested with dummy leads before going live. • Monitoring or alerting so we are notified if a workflow breaks or a lead has gone untouched for more than 2 hours. • Full written documentation of every workflow, automation, and integration built, in plain language we can hand to a future hire if needed. • A 30-minute live walkthrough/training call upon completion. Requirements • Demonstrated prior experience integrating Retell AI (or a comparable AI voice platform) with GoHighLevel. Please describe your specific integration approach in your application — this is the single most important qualifier for this role. • Strong working knowledge of GHL workflows, pipelines, Conversations, Social Planner, and custom fields. • Experience with webhook-based integrations and basic error handling / fallback logic. • Prior experience in healthcare, home services, senior care, or another high-urgency, high-trust service business is a strong plus. • Clear, responsive communication — we will be working closely together through build and testing. How to apply 1. Confirm you have integrated Retell AI (or similar) with GoHighLevel before, and briefly describe how you approached it. 2. Share 1–2 examples of GHL builds you've done for service businesses, ideally with multi-channel lead nurture. 3. Provide your estimated timeline and a flat-fee quote for the full scope above (we prefer fixed pricing over hourly for this project). 4. Let us know your availability to start. We have a detailed internal spec (pipeline stages, message templates, and workflow logic) ready to share with serious candidates upon request.

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.

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

Forum Intelligence: Project Brief & Initial Rollout 1. Executive Summary & Objective Forum Intelligence is a beginning as a localized data retrieval, processing, and archiving system designed to scrape public municipal records and state legislative data for public oversight. The immediate objective is to build a functional, highly resilient prototype focused on the Tri-Cities region (Burbank, Glendale, and Pasadena, California). The system will autonomously ingest messy, unstructured municipal data (City Council meeting minutes, agendas, public notices, and legislative PDF text, recorded mp4), clean it, and make it fully searchable and queryable via a localized AI agentic framework. 2. Phase 1 Scope: The Tri-Cities Rollout Th engineer will be responsible for building two primary pillars: A. Resilient Scraper Bots • Target Ingestion: Monitor and pull data from Burbank, Glendale, and Pasadena municipal portals and California legislative feeds. • Data Types: Brittle HTML sites, heavily nested tables, public notices, legislative drafts, and massive unstructured PDF archives. • Requirements: The scraping architecture must be exceptionally robust, utilizing intelligent error handling, retry semantics, and pagination tracking to handle frequent municipal website layout changes without breaking the pipeline. B. Ingestion & Vector Pipeline • Parsing: Extracting clean text from poorly formatted documents and scanned PDFs. • Local RAG (Retrieval-Augmented Generation): Chunking and embedding the data locally into a vector database (e.g., pgvector, Chroma, or Milvus) to enable semantically accurate entity linking and contextual search. 3. Targeted Hardware Stack To ensure maximum data security, strict public oversight integrity, and predictable operational costs, Forum Intelligence is skipping commercial cloud APIs in favor of an on-premise, localized NVIDIA enterprise deployment. The production roadmap aligns precisely with the new computing patterns detailed in NVIDIA’s latest hardware roadmap: • Inference & Token Generation: Running local open-weight frontier models (e.g., Neotron 3 Ultra or Claude/Llama equivalents) optimized for reasoning and long-context tool use. • Compute & Orchestration: The backend infrastructure is architected around NVIDIA’s dedicated agentic architecture, utilizing high-instructions-per-clock (IPC) Vera CPUs paired with Vera Rubin GPUs. • Memory & Storage Processing: Utilizing NVIDIA’s unified memory fabric and data processing units (DPUs) for ultra-low latency context management, KV caching, and fast vector database retrieval. 4. Immediate Milestones for the Engineer 1. Architecture Design: Map out the database schema and local inference ingestion loop. 2. Tri-Cities Scraper Deployment: Write and deploy the initial automated bots for Burbank, Glendale, and Pasadena. 3. Local MVP Pipeline: Demonstrate a local RAG pipeline where a user can query the Tri-Cities scraped records and receive grounded answers with exact source attributions. The above was AI generated from months long conversations with Gemini. The goal is to prove the concept then roll out to LA County, state of CA, and then the country.