Senior Forward Deployed AI Engineer (GenAI, AWS)

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. You’ll be measured on whether the Business Unit’s number moved — not on hours, not on scope delivered. This is a role for engineers who have led before — as a founder, a CTO, a staff engineer — and who want to stay in the code while owning the outcome. On most days you’ll be the most senior technical person in the room, and you’ll still be the one shipping.

Responsibilities

• Take the operator’s seat. Spend weeks doing someone else’s job (e.g., claims processing, underwriting, revenue-cycle work) before writing code
• Learn domains quickly to become conversant in unfamiliar business functions and argue with domain experts
• Ship GenAI/LLM systems to production, handling challenges beyond the prototype phase
• Build or own evaluation suites for non-deterministic systems, defining measurable success criteria
• Work autonomously in unfamiliar codebases or languages, demonstrating strong engineering fundamentals
• Deliver cloud-native solutions on AWS (GCP/Azure a plus) using containers, Kubernetes/ECS, IaC, CI/CD
• Engage credibly with senior stakeholders, including BU heads and CTOs, in redesign and scoping conversations
• Navigate ambiguity and ownership, closing gaps in underspecified engagements by design
• Maintain strong AI/ML foundations to reason about model failure modes beyond API calls
• Leverage hands-on production experience with Claude Code/Cowork

Requirements

• 8+ years building software, with a substantial share writing production code you were accountable for
• Hands-on today and intend to stay that way — this role is for engineers who want to remain in the code
• Genuine willingness to spend weeks doing operational work (e.g., claims processing, underwriting) before coding
• Proven ability to ship GenAI/LLM systems to production, not just demos or notebooks
• Experience building or owning evaluation suites for non-deterministic systems
• Strong engineering fundamentals; productive in unfamiliar codebases or languages
• Proficiency in Python and/or TypeScript (depth matters more than stack)
• Cloud-native delivery experience on AWS (GCP/Azure a plus): containers, Kubernetes/ECS, IaC, CI/CD
• Ability to hold redesign conversations with BU heads and scoping conversations with CTOs
• Comfort with ambiguity and ownership; closing gaps in underspecified engagements
• Solid AI/ML foundations to reason about model failure modes
• Strong hands-on production experience with Claude Code/Cowork
• Fluent English, written and spoken

Nice to have

• Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution
• Real depth in one of our blueprint industries: financial services, insurance, healthcare, asset management
• Consulting, professional services, or other embedded customer-facing delivery experience
• Data platform depth: data lakes, warehouses, streaming/real-time analytics, data mesh, data contracts, governance, data quality
• MLOps and classical ML experience: PyTorch, SageMaker, MLflow
• Fine-tuning, distillation, or inference/serving optimization
• Graph databases (Neo4j, AWS Neptune)
• IaC depth: AWS CDK, CloudFormation, Terraform
• Open-source contributions or public writing on applied AI

Benefits

• Frontier delivery work across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare
• Opportunity to shape how leading enterprises adopt AI, from strategy through first deployment
• Forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers
• Growing AI delivery practice where you help build the tooling and frameworks, not just use them
• Remote-friendly culture