Senior Forward Deployed AI Architect (GenAI, AWS)
About The Position
Provectus is a Premier AWS partner and an Anthropic Strategic Partner focused on applied AI, helping enterprises leverage AI technologies like Claude and agentic systems to achieve measurable business outcomes. The company operates across North America, LATAM, and EMEA, working with clients globally in the Financial Services & Insurance and Healthcare & Life Sciences sectors. Provectus utilizes five pre-built AI Blueprints to re-engineer critical business processes. The Forward Deployed Architect (FDA) role involves embedding within client operations to understand, implement, and own the outcomes of AI solutions. This role emphasizes a hands-on approach, where the architect first performs the client's job before automating it, learning constraints from the inside. Key principles of the role include being embedded, focusing on real tasks rather than scope, and operating autonomously. Engagements start with existing industry blueprints, which are continuously improved based on field learnings. The success of the role is measured by the business unit's performance improvements, not just hours or scope delivered. This position is for experienced engineers who want to remain hands-on while owning the outcome, often being the most senior technical person in the room.
Requirements
- 8+ years of software building experience, with a significant portion in writing production code.
- Willingness to spend weeks performing an operator's job (e.g., claims processing, underwriting) before coding.
- Demonstrated ability to quickly learn and become conversant in unfamiliar business domains.
- Experience shipping GenAI/LLM systems to production, handling post-prototype challenges.
- Experience building or owning an evaluation suite for non-deterministic systems.
- Strong engineering fundamentals, with productivity in unfamiliar codebases or languages.
- Proficiency in Python and/or TypeScript.
- Cloud-native delivery experience on AWS (GCP/Azure a plus), including containers, Kubernetes/ECS, IaC, CI/CD, and operational handover.
- Credibility with senior stakeholders for redesign and scoping conversations.
- Comfort with ambiguity and ownership, as engagements are intentionally underspecified.
- Solid AI/ML foundations, understanding model failure modes beyond API usage.
- Strong hands-on production experience with Claude Code/Cowork.
- Fluent English, written and spoken.
Nice To Haves
- Prior experience as a founder, CTO, or engineering leader who returned to individual contribution.
- Deep expertise in financial services, insurance, healthcare, or asset management.
- Consulting, professional services, or other embedded customer-facing delivery experience.
- Data platform expertise: data lakes, warehouses, streaming analytics, data mesh, data contracts, governance, data quality.
- Experience with MLOps and classical ML tools like PyTorch, SageMaker, MLflow.
- Experience with fine-tuning, distillation, or inference/serving optimization.
- Experience with graph databases (Neo4j, AWS Neptune).
- Deep IaC experience with AWS CDK, CloudFormation, or Terraform.
- Open-source contributions or public writing on applied AI.
Responsibilities
- Take the operator's seat for two to four weeks at the start of an engagement to learn the function from the inside.
- Achieve working fluency in new domains like insurance underwriting or healthcare revenue cycle within weeks.
- Collaborate with operators and Forward Deployed Executives to redesign functions from first principles.
- Ship production GenAI systems, including LLM applications, agentic workflows, and retrieval/extraction pipelines, into customer environments.
- Build evaluation harnesses before features to ensure systems meet business KPIs.
- Write production code across the stack, including backend services, data pipelines, and the AI layer, using Python and TypeScript.
- Deploy systems to production on AWS (or GCP/Azure as required), ensuring they are containerized, observable, and maintainable.
- Utilize and contribute to industry blueprints, feeding field learnings back into them.
- Own the outcome by working with a Forward Deployed Executive to meet business unit KPIs.
- Drive adoption of systems, recognizing change management as part of the engineering job.
- Be credible with customer teams (engineers, operators, executives) and willing to challenge them.
- Shape and influence commitments before they are made, based on buildability.
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
- Forward-deployed model working in small, senior teams
- Growing AI delivery practice where you help build tooling and frameworks
- Remote-friendly culture
- High-impact role with direct visibility to leadership
- Strong earning potential with performance-based bonuses
- Opportunity to work with cutting-edge AI and cloud solutions
- B2B contract model or full-time model
- Unlimited Vacation policy
- Generous health, vision, and dental insurance
- 401(K) matching plan
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
