Forward Deployed AI Architect (GenAI, AWS)
Forward Deployed AI Architect embeds with clients to learn their workflows (e.g., insurance underwriting, healthcare revenue cycle) hands-on, then redesigns and builds production GenAI systems (LLM applications, agentic workflows) on AWS. Focuses on measurable business outcomes, evaluation-driven development, and long-term blueprint improvements.
- Compensation
- $200K–$250K / yr
- Location
- San Francisco Bay Area, California
- Work setup
- Remote
- Seniority
- Staff
- Employment
- Contract
- Experience
- 8+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- 8+ years building production software with hands-on accountability
- Willingness to spend 2-4 weeks doing the operator’s job (e.g., claims processing, underwriting) before coding
- Fast domain learning ability (e.g., insurance/healthcare workflows)
- Shipped GenAI/LLM systems to production (not demos/notebooks)
- Built/evaluated non-deterministic system evaluation suites
- Strong Python/TypeScript fundamentals and cloud-native AWS delivery (containers, IaC, CI/CD)
- Credibility with senior stakeholders (BU heads, CTOs)
- Comfort with ambiguity and ownership in underspecified engagements
- Production experience with Claude Code/Cowork
- Fluent English (written/spoken)
Full description
About the role:
Provectus is a Premier AWS partner and an Anthropic Strategic Partner at the forefront of applied AI, helping enterprises turn Claude, agentic systems, and their own data into measurable business outcomes through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide and are obsessed with reimagining how they operate and compete.
Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.
We embed engineers and leaders inside client operations as Forward Deployed Engineers (FDE) and Forward Deployed Executives (FDX) — people who learn the work, ship the system, and own the outcome. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Bluprints.
You will do the customer’s job before you automate it.
Most AI engagements fail the same way: someone gathers requirements, someone writes a PRD, and a team ships a workflow nobody uses. We think the requirements-gathering step is the bug. So we remove it.
A Forward Deployed AI Engineer at Provectus spends the first weeks of an engagement in the operator’s seat — as the underwriter, the analyst, the RCM specialist, the claims clinician, whoever actually does the work we’ve been asked to change. You do the job. You learn the constraints from the inside, the ones nobody writes down. Then you sit at a table with that operator and a Forward Deployed Executive and rebuild the function from first principles — and you are the one who builds it.
Three things define how you work:
- Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it.
- Real tasks, not scope. You are not fenced into a siloed deliverable. You go where the operating problem is.
- Autonomous. Embedded is not staff-augmented. You own the method; nobody hands you a ticket.
You won’t start from zero. Provectus builds industry blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it. That loop is the difference between an outcome and an invoice.