**SEO & AEO Strategist** **The role** As Lead SEO & AEO Strategist, you bring a strong SEO background with a deep understanding of AEO and you're the person who raises the analytical bar for the whole team. You are the analytical expert of the team and the voice everyone lean on to make sense of how they show up in AI prompts. You deeply understand our data, reading what's moving and why, and create an actionable plan of recommendations we can act on. You also set the standard for how the rest of the team reads the data and advises clients: mentoring analysts, building the playbooks others run on, and turning your judgment into something we can scale. This is a hands-on, data-first, client-facing role with a clear enablement mandate: you supply the analytical judgment, you deliver it as strategy, and you teach others to do the same. What you'll do Get our brand and clients up and running. Onboarding and get us and clients to value fast, so their accounts are working hard for them from week one. Read the data, find the signal. Analyze how client brands surface across AI answer engines. Identify citation gaps, ranking shifts, and the content patterns that move Share-of-Prompt and our other visibility metrics. Lead working sessions where you take a client's growth and brand goals and map them to a concrete AEO plan, then push on the parts that will move the needle most. Deliver insights and recommendations. Produce the briefs, performance reviews, and optimization plans clients rely on. Translate complex visibility data into clear narratives for both technical and executive audiences. Set the standard and level up the team. Mentor and train others on how to read the data, run a client session, and turn a messy dataset into a recommendation that lands. Define the analytical methods and quality bar others work to, and bring newer team members up to speed on AEO fast. Build the playbooks. Turn your judgment into reusable assets, including analytical frameworks, content playbooks, session templates, and ways of measuring what's working, so the pod's best thinking scales beyond any one person. Support Fix Pack work. Help diagnose what needs fixing and validate that deployed Fix Packs are moving the metrics they should. Flag the exceptions and opportunities that need the team's attention. Work shoulder to shoulder with the pod. Give the Partners and the wider pod the analytical inputs they need: the right numbers, the right context, the right recommended next move. Track the category. Stay current on AEO / SEO developments and how AI answer engines are evolving, so our recommendations stay ahead of a landscape that is constantly shifting. What you need to know (SEO / AEO) This is the foundation of the role. You should already think in terms of how brands earn visibility in AI answers, not just traditional search rankings, and be able to explain that thinking to others. SEO foundations. Solid, hands-on fundamentals: keyword and content strategy, structured data, site architecture, and organic performance analysis, with growing expertise in AI search. Metrics literacy. Comfort reasoning about visibility and performance metrics: reading a shift and understanding what it implies. Category awareness. Familiarity with the AI-visibility tooling landscape, or genuine eagerness to get up to speed fast. What you bring Advisory instinct. You're at ease guiding clients, walking them through a recommendation, and making a technical idea land for a marketing or brand team in plain language. A teaching mindset. You like making other people better at their craft. You can break down how you reached a conclusion, give useful feedback, and turn your own instincts into repeatable methods. Data fluency. Comfortable working with data to find signals. You don't just report numbers, you interpret them. Prompt literacy. Familiarity with prompt engineering and LLM behavior, enough to work effectively inside agent workflows and reason about their outputs. Storytelling. Strong written and verbal communication. You can turn a messy dataset into a clear recommendation for a stakeholder who has thirty seconds. Organized under load. Proven ability to juggle multiple accounts and deadlines without dropping quality. Detail obsessed. Every lift, every point of impact piques your curiosity. Resourceful and proactive. A self-starter who finds creative solutions, adapts quickly, and is comfortable navigating ambiguity and learning new tools. Who you likely are * 4+ years of hands-on SEO or organic-growth work behind you. Agency pedigree is a plus or a comparable data-heavy, client-facing role at a SaaS or AI company. * Someone with an SEO or digital-marketing background who is leaning hard into AI search, or a sharp analyst who's genuinely excited about the AEO category. * Confident on a client call, in a working session, or in a written recommendation, and used to high-touch accounts. * Someone others naturally come to for answers. You've informally or formally mentored, trained, or set the bar for teammates before. * A craftsperson who takes pride in the details while keeping the big picture in mind. * Looking for a role with a clear growth path toward deeper technical and team leadership. 
 Bonus points * You've built reusable things for clients or teams before: playbooks, content frameworks, onboarding material, or ways to measure what's working. * You've worked with enterprise or other high-touch accounts. * You've operated inside a fast-moving, startup.

I’m looking for an AI Engineer to help build an automated red-teaming product based on open-source models. This is a short-term, hands-on project for around 2 months, with an expected commitment of about 20 hours per week. The goal is to build a specialized red-teaming engine that can generate adversarial prompts across different risk domains, severity levels, and attack strategies — then automatically run those prompts against target AI models to identify bad cases, failure patterns, and safety gaps. 🔍 What you’ll work on Build red-teaming systems on top of open-source LLMs, including fine-tuning, prompt optimization, evaluation pipelines, and model orchestration. Design automated prompt generation workflows across risk domains such as self-harm, hate, violence, sexual safety, misinformation, fraud, cyber, and other high-risk areas. Generate prompts across different harm levels, from benign edge cases to policy-borderline and clearly unsafe scenarios, while maintaining structured taxonomies and evaluation criteria. Run automated tests against target models such as Gemma, Llama, Qwen, or other open-source / closed-source models to surface jailbreak patterns, over-refusal, under-refusal, and policy inconsistencies. Build feedback loops that turn model failures into stronger red-team prompts, improved eval sets, remediation recommendations, and continuous safety testing. 🧠 What I’m looking for Hands-on experience with open-source LLMs, fine-tuning, LoRA / QLoRA, RAG, model evaluation, and LLM inference pipelines. Familiarity with AI safety, red teaming, adversarial prompting, jailbreaks, safety evals, or trust & safety systems. Ability to build end-to-end systems, including data pipelines, model serving, eval harnesses, scoring, dashboards, and automation workflows. Bonus if you’ve worked on model safety, content moderation, policy evaluation, agentic testing, or automated eval infrastructure. ⏳ Project setup Duration: around 2 months Time commitment: about 20 hours per week Format: flexible / remote-friendly Stage: early-stage build, from 0 to 1 🚀 Why this is interesting This is not about manually writing red-team prompts one by one. The goal is to build a scalable system that can continuously generate, test, categorize, and learn from model failures — helping teams understand where AI models break, why they break, and how to improve them. If you enjoy working with open-source models, AI safety, red teaming, and fast 0-to-1 product building, I’d love to chat. Feel free to DM me if this sounds like you, or if you know someone who might be a good fit.

Job Description: Note: this is about Claude (Anthropic), used by multiple people on our team — not Microsoft Teams integration. This is coaching, not a build-it-for-us project — you'll teach our exec how to do this himself, not deliver a finished system. We're looking for a Claude (Anthropic) super-user to coach a busy executive 1:1 on setting up Claude for team-wide use — shared Projects, Google Drive sync, and ongoing customization — so our team gets consistent, reliable output without him having to rebuild things every time source documents change. This is live, hands-on coaching — not a course, and not a hand-off deliverable. You'll walk him through his actual setup in real time (screen share), show him how to fix and structure it, and leave him able to run it himself. What you'll do: Walk the executive through, live, how to structure shared Claude Projects so multiple team members get consistent, non-conflicting output Show him how to connect and sync Google Drive content into Claude Projects so materials stay current without manual re-uploading Teach him a repeatable process so future document updates reliably reflect in Claude Coach him on customization (Skills, project instructions, memory) for consistent output across the team Leave him with clear, documented steps he can run himself or hand off to someone else What we need from you: Hands-on experience setting up Claude (Anthropic) Projects in a business/team context, including Google Drive sync Strong ability to teach a non-technical executive live — walking him through it, not just doing it for him Comfortable coaching over video/screen-share Bonus: experience rolling out Claude across a team or organization, not just for individual use In your proposal, include an example of a team-based Claude setup you've built — what it did and how you kept it current. Engagement details: 4 hours/week, live sessions, for 2 weeks (8 hours total) — flag in your proposal if you think this scope needs adjusting Video call with screen share, flexible scheduling $80–125/hr depending on experience Possible extension if it's a good fit

Colony Mobility LLC is a Florida-based technology company preparing a Phase I Small Business Innovation Research (SBIR) proposal for the U.S. Department of Transportation under Topic 26-FT1: Person-Centered, Carefree, Complete Trip Planning — Powered by AI. We are seeking a Senior AI Systems and Algorithm Researcher to serve as a named research subcontractor on this federal proposal. This is a research design and documentation role — no production software build is required. What you will research and document: Rider preference engine algorithm — design a machine learning system that learns individual traveler needs over time, including stated preferences, observed behavioral patterns, and inferred preferences for new users Success probability mathematical model — design and write a proof of correctness for a weighted scoring algorithm that calculates the probability a specific rider will successfully complete a specific trip given real-time conditions AI orchestration architecture — document the multi-agent coordination system that assembles, monitors, and replans multimodal trips in real time Outcome learning algorithm — design the reinforcement learning loop that improves system recommendations based on real trip outcomes Trip assembly algorithm pseudocode — document the step-by-step logic for building complete door-to-door journeys from multiple transportation sources LLM integration architecture — document how large language models are used within the system for normalization, preference reasoning, and conversational interfaces What the federal report specifically requires from this role: Algorithm pseudocode for all AI components Mathematical notation and proof of correctness for the success probability model Summary of how ML methods have been used to solve trip-planning problems similar to this solicitation — literature review contribution Justification of how prior research is extended and improved by this system What we need from you before July 3, 2026: A short professional bio (3–5 sentences) describing your relevant background A brief letter of commitment confirming your availability and intent to perform the described work if the contract is awarded Required qualifications: Graduate degree (Master's or PhD) in Computer Science, Applied Mathematics, Data Science, or Artificial Intelligence — or equivalent research experience Demonstrated experience designing machine learning algorithms — preference learning, recommendation systems, optimization, or routing Ability to write mathematical notation fluently — probability models, weighted scoring functions, proofs of correctness Experience writing technical research documentation — academic papers, federal research reports, or technical deliverables for a non-technical audience Familiarity with large language models and their practical limitations in production research contexts Strong plus (not required): Background in multimodal routing algorithms, operations research, or transportation optimization Experience with reinforcement learning or multi-agent systems Prior SBIR, federal research, or government contract experience Published research on routing algorithms, preference learning, or mobility AI Contract details: Hours: 180 hours over 6 months Rate: $120/hour Location: fully remote Start date: September 2026, upon DOT SBIR Phase I award notification Total contract value: $21,600 plus 20% overhead = $25,920

Real Estate Acquisitions Coach — Test & Refine AI Voice Agents We have AI voice agents (inbound, outbound, and speed-to-lead for web leads) that handle motivated seller calls for a real estate investment company. They work — but we need them to sound like a real acquisitions rep, not a bot. **You'll:** - Call into and receive calls from our agents as different seller personas - Try to break them, then tell us what's off - Rewrite robotic lines with language a real rep would use - Flag missing discovery questions and weak objection handling **You are:** - A real estate acquisitions rep / ISA / wholesaler with thousands of seller calls under your belt - Experienced across inbound, outbound, and web lead follow-up - Able to explain *why* a line lands or doesn't **Start:** Paid test / 5 mock calls with Video feedback. Ongoing work if it's a fit. **To apply, send:** 1. How many seller calls have you personally handled? 2. Your best opening line for a 60-day-old lead 3. Your hourly rate Not looking for prompt engineers or copywriters — looking for an operator who's lived in these calls.

We are looking for an experienced AI Voice Developer to build AI receptionists for service-based businesses. This will be an ongoing relationship, not just a one-time project. If you do great work, we expect to send multiple clients every month. Responsibilities Build an AI receptionist that can: Answer inbound phone calls 24/7 Hold natural conversations using an LLM Answer business FAQs Book appointments into the client's booking software/CRM Transfer calls to the business owner when appropriate Send SMS confirmations and follow-up messages Respond to incoming customer text messages Integrate with APIs when needed (BookingKoala, GoHighLevel, HubSpot, Calendly, etc.) Test and optimize the AI before delivery Requirements Experience with Vapi, Retell AI, Bland AI, or similar voice AI platforms Experience integrating CRMs and booking systems through APIs Strong understanding of prompt engineering for voice agents Ability to troubleshoot and improve call quality Excellent communication Ability to deliver projects within 3–7 days To Apply Please answer the following: Which voice AI platforms have you built on? How many AI receptionists have you built? Have you integrated booking software or CRMs before? Have you worked with BookingKoala? Please send 2–3 demo phone numbers or videos of AI receptionists you've built. What is your flat-rate price per AI receptionist? What do you charge monthly for ongoing support? We are looking for a long-term white-label partner who can fulfill projects as we bring in new clients.

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.

We're looking for a developer to build a lean, working Proof-of-Concept of an automated pipeline that ingests podcast episode audio, generates a clean transcript with speaker diarization and timestamps, and uses an open-source NotebookLM alternative (Notex or Open Notebook) to automatically produce a suite of repurposed content assets — show notes, episode summaries, social media posts, blog drafts, and pull quotes. The goal is to validate the end-to-end workflow on 2–3 sample episodes, not to build a full production platform yet. We want to see the plumbing work cleanly before investing in scale. Envisioned stack: n8n for orchestration, a speech-to-text API (Deepgram, AssemblyAI, or Whisper), a lightweight DB (Supabase or PostgreSQL), and an open-source NotebookLM alternative as the content generation engine. The whole system should be self-hostable via Docker. We're open to the developer's recommendations on the best tools and tradeoffs. Deliverables include a working n8n workflow, Docker-compose setup, a short README, demonstration on 2–3 sample episodes we provide, and a brief written recommendation on Notex vs. Open Notebook for scaling this pipeline to ~500 episodes/year. Required skills: n8n (or similar orchestration), speech-to-text APIs, Docker / self-hosted deployments, hands-on experience with NotebookLM alternatives or RAG-based content engines, LLM prompt engineering for structured output, and PostgreSQL / Supabase basics. Nice to have: Prior podcast or media-tech automation work, pgvector / RAG experience, structured output via JSON schema or function calling, and experience scaling automation pipelines. To apply, please include: a short overview of your automation / AI pipeline background, specific experience with n8n + STT APIs + open-source NotebookLM alternatives, links to GitHub or prior workflows, a 2–3 sentence note on whether you'd recommend Notex or Open Notebook for this use case and why, and your estimated turnaround time. This is a fixed-budget POC (~$100). If the workflow is clean, reliable, and well-documented, we plan to expand it into a full production build (client portal, human-in-the-loop editor, admin dashboard, scaling to 500+ episodes/year) with a significantly larger budget.

We are not looking for someone to create a single avatar. We are looking for a long-term creative partner to help build one of the world's most recognizable AI media brands. If you're excited about combining AI, storytelling, and positive global impact, we'd love to hear from you. Bonus experience: News media Animation Digital influencers Entertainment branding Intellectual property development To Apply Please include: Your portfolio of AI characters. Examples of consistent AI characters you've developed. The AI tools you use most often. Your process for maintaining character consistency across thousands of images and videos. Your favorite AI character you've created and why. A brief description of how you would design a globally trusted AI news host. Finalists will complete a paid concept assignment. Design one original AI news host for Global Positive News that includes: One hero portrait Three alternate expressions A short biography A sample script introducing the character Three example prompts showing how the character can be recreated consistently

Seeking a LLM prompt engineer and solutions architect to develop AI medical note writing templates. The role involves creating structured templates for clinical documentation. Patient encounters will be turned into precise medical notes with good detail and reproducible note sections based on previous patient encounters. Also complete testing to ensure notes are compatible with my medical record system. The ideal candidate will have experience in medical documentation and AI solutions architecture.