Senior AI Engineer

What you’ll do:

Spend the first weeks of each engagement in the operator’s seat, learning the constraints from the inside, then rebuild the function from first principles alongside the client and a Forward Deployed Executive — and you are the one who builds it.

Be part of the customer’s team, inside their process; work on real tasks, not scoped deliverables, and own the method autonomously.

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.

Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare.

Help shape how leading enterprises adopt AI, from strategy through first deployment; help build the tooling and frameworks of a growing AI delivery practice.

What we look for:

Typically 7+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way.

Genuinely willing to spend time understanding someone else’s job before writing code; demonstrated ability to become conversant in an unfamiliar business function quickly.

Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works.

You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why.

Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack.

Cloud-native delivery on AWS (GCP/Azure a plus), including the operational reality of a system someone else inherits.

Pre-sales experience. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room.

Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job.

Hands-on experience with Claude, Claude Code, and Cowork (skills, workflows, MCP, integrations, connectors, custom harnesses).

Nice to have:

Containers and orchestration (Kubernetes/ECS) and CI/CD in production.

IaC depth: AWS CDK, CloudFormation, Terraform.

Open-source contributions or public writing on applied AI.

What we offer:

Full-time.

On-site visits to client’s facilities and our office in NYC 1/week

Unlimited Vacation policy.

Generous health, vision, and dental insurance.

401(K) matching plan.

Base salary $180k–$200k + bonuses; OTE up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, and abilities of the applicant, and alignment with market data.

*No Visa sponsorship

We’re real

A person reads your application. We filter out AI-generated and fraudulent submissions automatically. Every application that clears that filter is read by someone on our team.
We may ask for a quick ID verification. Fraudulent applications are common, and this protects real candidates.
You’ll meet the people you’d work with. We host AI engineering events in New York and San Francisco. We'd be happy to talk in person. Your interviews are with Pavel Borobov, Solutions Architect, and Stepan Pushkarev, Co-Founder & CEO.

How we hire:

1. Recruitment interview.
2. Tech interview with our FDE (30 min).
3. A live engineering building session (1.5 hours). We hand you a business function and the constraints. You have to understand the job and rebuild it — then say what you’d build and how you’d know it worked.       Use AI the way you normally would; we expect AI-generated code. What we look at is how you used AI, the judgment behind your choices, and what you researched beyond what any LLM already knows.
4. Soft skills interview.
5. Offer discussion.