AI Architect

Provectus•San Jose, CA

16h•$180,000 - $200,000

About The Position

Provectus is hiring a hands-on AI Architect to embed with enterprise customers in regulated industries such as financial services and healthcare. The architect learns how operators work and what constraints they face, then rebuilds functions from first principles alongside the client and a Forward Deployed Executive, building and deploying production AI systems rather than delivering prototypes or slide decks. The role includes work across Cowork Activation, Agentic SDLC, and Blueprint Activations. Provectus provides industry Blueprints based on systems already shipped for customers; the architect starts from those baselines and feeds lessons from engagements back into them. The position also helps enterprises adopt AI from strategy through first deployment and contributes to the tooling and frameworks of a growing AI delivery practice.

Requirements

Typically 7+ years building software, including substantial production coding for which the candidate was accountable.
Currently hands-on and intending to remain hands-on.
Willingness and demonstrated ability to understand another person’s job and become conversant in an unfamiliar business function quickly.
Experience shipping GenAI/LLM systems to production, including addressing challenges beyond the prototype stage.
Experience building or owning an evaluation suite for a non-deterministic system, and ability to explain what was measured and why.
Strong engineering fundamentals and ability to become productive in an unfamiliar codebase or language.
Proficiency in Python and/or TypeScript.
Cloud-native delivery experience on AWS, including operational considerations for systems inherited by others.
Pre-sales experience and credibility with senior stakeholders, including business-unit leaders and CTOs.
Comfort with ambiguity, ownership, and engagements that begin underspecified.
Hands-on experience with Claude, Claude Code, and Cowork, including skills, workflows, MCP, integrations, connectors, or custom harnesses.

Nice To Haves

Containers and orchestration experience, such as Kubernetes or ECS, and production CI/CD.
Infrastructure-as-code depth with AWS CDK, CloudFormation, or Terraform.
Open-source contributions or public writing on applied AI.
Experience with GCP or Azure.

Responsibilities

Spend the first weeks of each engagement learning the operator’s work and constraints from inside the organization.
Rebuild business functions from first principles alongside the client and a Forward Deployed Executive, and build the resulting systems.
Work as part of the customer’s team and process, owning the method autonomously from problem framing through production.
Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare.
Use Provectus industry Blueprints as a starting point and contribute field learnings back to them.
Help leading enterprises adopt AI, from strategy through first deployment.
Help build tooling and frameworks for the AI delivery practice.