We're not hiring employees.
We're assembling
the A-team for the agentic era.
Nine specialist roles. Project-based. Remote-first. Vetted through talent.myndQ.ai, paid like specialists, deployed against regulated-industry work that ships in production.
contractor
promise
01Trust
Day rates posted. NDAs you can read. No bait-and-switch on scope after you sign.
02Transparency
You see the client, the budget, and the success metrics from day one. No middleman tax.
03Candidate Experience
Screening via myndQ takes 90 minutes, two rounds. Instant transparent scoring with clear feedback. Top scores and qualified counts published on job leaderboard.
Three industries.
One throughline: regulated, complex, expensive to get wrong.
We don't take work in industries we can't ship in. The pipeline you're applying to gets deployed against three sectors where AI judgment matters more than AI hype: financial services, healthcare and pharma, and energy and manufacturing. Industry depth pays a premium on every role, in every tier. If you've shipped inside one of these, tell us in your application.
Financial Services
Banks, insurers, asset managers, fintech. The places where one hallucinated number creates a regulatory paper trail.
Healthcare & Pharma
Payers, providers, life sciences R&D, medical devices. Where AI meets PHI, FDA, and a patient on the other end.
Energy & Manufacturing
Utilities, oil and gas, industrial manufacturing, advanced supply chain. Where AI meets OT systems, plant safety, and ESG reporting.
AI Diagnostic Lead
You're the person in the room when the CEO asks, "what should we actually do about AI?" You interview their leaders, audit the stack, separate signal from vendor noise, and walk out with a 12-month roadmap the board will fund. We hand you the engagement. You hand us a brief that closes the next three.
- Lead 8 - 12 leader and operator interviews per engagement, mostly C-suite and VP-level
- Audit AI/data stack, shadow tool usage, and data flow risks
- Rank the top 3 opportunities by ROI, time-to-value, and execution risk
- Write the board-ready brief and present it to the exec team
- Hand off cleanly to the Build squad with a scope they can sprint against
- 10+ years in strategy consulting, transformation, or operator C-suite (CTO/CDO/CIO)
- You've run AI or digital programs end-to-end, not just slides
- You can disagree with a CEO in week one and still close the engagement
- Excellent written English. The brief is the deliverable.
Specialists, not seats.
Every contractor in this pipeline is a single point of leverage. One person who can lead a Diagnostic. One who can architect a RAG stack. One who's debugged enough drift incidents to know what's worth a 2am page. We pay accordingly.
- You're paid per outcome or per engagement, not per hour. Done early = full fee.
- Work flows through hr.myndQ.ai so the matching is fast, fair, and documented
- You can take or pass on any engagement. No exclusivity unless we both want it.
- Rate cards are public-internal. You'll know what every other contractor on your project is making.
- You ship. Production code, real briefs, things that actually run.
- You write things down. Our IP is the playbook, not the person.
- You behave like an owner with the client. We don't manage humans, we coordinate adults.
Agentic AI Engineer
You build the multi-step agents that actually do work. Claims triage. Lead qualification. Document review. The kind of thing where one bad output costs the client money and trust, so you obsess over tool design, escalation paths, and the boring 80% of failure modes nobody demos.
- Architect agent workflows using Claude, GPT, or open-weight models per client constraints
- Design tool integrations and human-in-the-loop handoff points that work in messy reality
- Ship to production with proper logging, eval harnesses, and cost monitoring on day one
- Pair with the client team. Nothing leaves as a black box. Documentation is part of the job.
- Production experience with at least one major model API and one agent framework (LangGraph, CrewAI, custom)
- Strong Python or TypeScript. Comfortable with async, queues, and tool-use patterns.
- You've broken things in prod and know how that shapes design decisions
- Bonus: experience with MCP, Anthropic's tool-use, or function-calling at scale
RAG & Data Pipeline Architect
Every AI system the client wants depends on data they don't think about. You're the person who fixes the ingestion, the chunking, the embeddings, and the retrieval, so the model has a fighting chance. Less glamorous than agents. Twice as important.
- Audit source data and remediate quality issues before they become hallucination problems
- Design and ship RAG pipelines: chunking, embedding, retrieval tuning, re-ranking
- Set up vector stores and the access controls/permissions that keep them safe
- Build the eval harness that proves retrieval is actually working, before the model gets blamed
- Strong data engineering chops: SQL, Python, batch and streaming pipelines
- Hands-on with at least two vector DBs (pgvector, Pinecone, Weaviate, Qdrant, Turbopuffer)
- You've tuned a real retrieval system and have opinions about chunking strategies
- Bonus: experience with Snowflake, Databricks, or enterprise data lake architectures
AI Evals, Guardrails & Governance Specialist
Most consultancies skip this. We don't, because it's where our retention comes from. You build the eval suites, the red-team scenarios, the guardrails, and the audit trails that let a CIO or CISO actually sign off on production AI. You also write the policy doc that matches.
- Design custom eval suites tied to the client's actual use cases and risk tolerance
- Run red-team scenarios and adversarial testing across prompt-injection, jailbreaks, and PII leakage
- Implement output guardrails, content filters, and the audit-logging architecture behind them
- Build the executive dashboard that tells the board "your AI is healthy" with actual numbers
- Map the work to EU AI Act, NIST AI RMF, sector-specific frameworks (HIPAA, SOC2, FINRA)
- Background spans security, ML ops, or AI safety. Pure ML researchers welcome if you've shipped to prod.
- You've built or maintained an eval framework (LangSmith, Braintrust, Inspect, custom)
- You read regulation for fun. Or at least, you read it before the client asks.
- Bonus: red-team experience or an AI safety/security cert
AI Adoption & Change Designer
Most AI rollouts don't fail at the model layer. They fail because the people who were supposed to use the thing didn't change how they worked. You're a hybrid: part instructional designer, part change consultant, part workflow engineer. You make adoption the thing the client brags about.
- Design role-specific training programs that go beyond "here's a prompt template"
- Map the current workflow, the future workflow, and the messy transition between them
- Build prompt libraries, playbooks, and the change-comms exec team needs to back the rollout
- Set up adoption tracking. Coach the team for the first 60 days post-launch.
- Background in change management, L&D, or org design. ADKAR or Prosci a plus, not required.
- Hands-on AI fluency. You use the tools daily, not just talk about them.
- You can write a one-page comms note the CEO will actually send
- Bonus: domain depth in healthcare, financial services, or large-team ops
Fractional AI Operations Lead
You're the person who keeps shipped systems alive. Drift monitoring, prompt and eval tuning, vendor change management, monthly exec readouts. You operate as a fractional AI Ops lead across 3 - 5 client accounts at a time, with your own playbook and dashboard rhythm.
- Own the monthly health report and exec readout for assigned client accounts
- Run bi-weekly iteration sprints: prompt tuning, eval refresh, cost optimization
- Catch and triage drift, vendor model swaps, and regression incidents before they hit customers
- Be the named operator the client Slack channels reach when something feels off
- You've operated AI or data systems in production for 3+ years. SRE, DevOps, MLOps backgrounds all welcome.
- You can write an exec update that doesn't sound like a tool screenshot
- You like steady work over hero work. Annuity-shaped, not project-shaped.
- Bonus: experience with Datadog, Helicone, LangSmith, or custom obs stacks for LLM apps
Steady cash. Real work. No re-selling yourself every 8 weeks.
- $12k - $28k MRR per client account, you keep ~70%
- 3 - 4 accounts = comfortable six figures, with capacity left over for Build sprints
- Renewal is the default. Most Run accounts run 18+ months once they go live.
- Year-2 contractors get first right of refusal on Co-Pilot tier engagements
- One async case study (90 mins, paid)
- One conversation with the Diagnostic Lead who'd hand you accounts
- One trial month on a small account before you're routed to bigger ones
Vertical Solutions Lead - HR & Talent
Dual-purpose role. You'll lead AI-for-People-Ops engagements for clients (resume triage, JD optimization, interview prep, onboarding copilots), AND you'll feed the roadmap for our own talent platforms hr.myndQ.ai and talent.myndQ.ai. You see what hurts in the field, we ship product against it.
- Lead the HR vertical accelerator engagements end-to-end (typically 6 weeks, $85k+ packages)
- Translate field learnings into product feature requests for the myndQ team
- Run the trust framework for AI-conducted interviews. Get the bias review and audit trail right.
- Co-author thought leadership on agentic-era hiring (we'll publish, you'll get the byline)
- 10+ years across HR tech, talent acquisition leadership, or HR transformation consulting
- Strong AI fluency. You can scope an agent build even if you don't write the code.
- You care about candidate experience as much as recruiter throughput
- Bonus: experience hiring inside FinServ, Health/Pharma, or Energy/Mfg, where compliance overlays change the playbook
Brand & Content Strategist - AI Category
Our pipeline runs on differentiated thought leadership, not paid ads. You'll own the content engine: research briefs, LinkedIn carousels, the diagnostic tool funnel, and the campaign architecture that turns a 2026 AI Readiness Brief reader into a booked diagnostic. You write like an executive talks, not like a copywriter trying to sound smart.
- Run the editorial calendar across blog, LinkedIn, briefs, and the AI Success Pack collateral
- Brief and oversee designers on carousel and asset production. We've already got the brand system.
- Build content-to-conversion funnels: research brief → diagnostic tool → booked consult
- Coordinate with the Vertical Solutions Leads to surface field stories worth publishing
- 5+ years in B2B content strategy. You've run a content engine that drove pipeline, not vanity metrics.
- Sharp opinion on the AI category. You can tell good thought leadership from recycled vendor talk.
- You write fast and edit ruthlessly. You're comfortable using AI as a co-author, not a crutch.
- Bonus: experience with HubSpot, WordPress, LinkedIn analytics, and SEO for B2B
Regulated Industries Lead - FinServ, Health, Energy
You're the person we put on every engagement in a regulated sector. You translate between the AI engineers, the compliance officers, the model risk team, and the auditor who shows up next Q. Less about writing policy from scratch, more about making sure what we ship maps cleanly to the framework the client has to defend.
- Sit in on every Diagnostic in financial services, healthcare/pharma, or energy/manufacturing
- Pre-clear the Build squad's architecture decisions against the client's regulatory posture, before code gets written
- Own the audit trail and documentation pack that turns a Build deliverable into something a regulator can review
- Run quarterly compliance refresh for Run-tier accounts: new rules in, controls updated, board memo out
- Co-author sector-specific thought leadership ("AI under SR 11-7," "GxP-grade copilots," "OT/IT AI convergence")
- Background in financial regulation, healthcare compliance, or industrial cybersecurity. Lawyers, ex-regulators, ex-Big-4 risk partners welcome.
- Strong technical literacy. You can read an architecture diagram and ask the right questions.
- You've shipped at least one regulated AI/ML system through audit. Once is enough. Twice is preferred.
- You have professional currency: CIPP/E, CISA, PMR, FRM, RAC, or equivalent. We don't care which, we care that you've earned one.
Most consultancies bolt compliance on at the end. We let it shape the work from day one.
- Pre-empts the most expensive failure mode: a Build that ships, a customer issue surfaces, and the client realizes there's no audit trail
- Turns the "AI risk" conversation into a sales advantage. We close FinServ and Pharma deals Big 4 firms don't even bid on.
- Shortens the Diagnose-to-Build handoff by 2 - 3 weeks. The compliance review happens in parallel, not after.
- Becomes the named expert on our content engine. Bylines on briefs, podcast invites, conference panels.
- You have veto power on architecture choices for regulated clients. Engineers know that.
- You're not the compliance department's nag. You're the engineering team's senior partner.
- You're never billable on a project where you can't be effective. Better for everyone.
Which role gets deployed where, and how often.
Industry depth is rewarded everywhere on the bench. This is roughly how the demand splits across the three sectors we serve, based on Q1 - Q2 2026 active and forecast pipeline.
Four steps. Real work in your hands as soon as you're ready.
The process is short on purpose. Long screening pipelines are how you lose senior people. We do enough to know you can ship, then we put work in front of you. If something doesn't fit, we tell you why and move on, fast.
Apply
Submit through talent.myndQ.ai. No cover letter. Pick the role, paste links, answer three questions about a real project.
AI screen
Role-specific screening conducted by myndQ. Instant transparent scoring, clear feedback. Top scores show on the public job leaderboard.
Human conversation
One call with the Diagnostic Lead or Vertical Lead who'd actually staff you. We answer your questions about the work and the rate.
First project
You're on the bench. We match you to a real engagement, brief you in, and you start. You can pass on it. We won't take it personally.
What contractors actually want to know before they apply.
Why is the screening done by an AI, and what does the leaderboard actually do?
Are these actually 1099 / contract roles, or "contract-to-hire" bait?
I'm not based in the US. Does that disqualify me?
How do you actually decide the rate?
What happens if a client wants to hire me directly?
Can I work for other consultancies while on the bench?
I have industry depth (FinServ / Health / Energy) but my AI tooling is rusty. Worth applying?
What if I'm strong in one area but green in another?
Ready to do
the work that
actually ships?
One application form. One AI-conducted screen. One human conversation. Then real work, on real engagements, with rates you can read out loud. The 2026 cohort is forming now.
Get on the bench
- Pick from 9 specialist roles
- Public-internal day rates, no negotiation theatre
- Industry depth premiums for FS, Health, Energy
- Pass on any engagement, no penalty