Senior AI Engineer

Provectus; San Francisco (CA); Vor Ort; USD 180.000 - 200.000; Vollzeit

Benefits dieser Stelle

Unlimited Vacation

Health insurance

401(K) matching

Office visits NYC 1/week

Zusammenfassung

Provectus in San Francisco is seeking an experienced software engineer to build Claude-enabled AI systems in production for financial services, healthcare, and other regulated industries. You’ll embed with client teams, learn their constraints, and ship real code rather than slides.

You’ll own projects from framing to deployment, collaborate with senior stakeholders, and tackle non-trivial ML/LLM challenges.

Qualifikationen

• Typically 7+ years building software with production responsibility.
• Hands-on today and committed to staying hands-on.
• Shipped GenAI/LLM systems to production, not demos.
• Experience with Claude, Claude Code, and Cowork workflows.
• Strong engineering fundamentals and ability to learn new domains quickly.

Aufgaben

• Deliver production-grade Claude-enabled AI systems for clients.
• Embed with customer teams, learn constraints, and ship from first principles.
• Own the development lifecycle from framing to deployment.
• Engage with senior stakeholders on redesigns and scoping.

Kenntnisse

Python

TypeScript

AWS

Claude/LLM

Pre-sales

Tools

Kubernetes

CI/CD

Terraform

AWS CloudFormation

Jobbeschreibung

About us

At Provectus , you don’t prototype in a sandbox and hand a client a slide deck. You embed inside a bank, an insurer, or a health system, learn the work, and ship a Claude + AWS system into their real, regulated production — then you watch the business number move. We’re an Anthropic and AWS Partner with 150+ certified architects. That means the newest models, real budgets, and problems that matter — without the layers, politics, and years-to-impact of a hundred-thousand-person firm. 350+ builders, 100+ customers in production, founder-led since 2010, offices across North America, LATAM, and EMEA.

Why Provectus

• Frontier access — Anthropic Preferred Partner: newest Claude models, real budgets, real problems.

• Real tasks (not scope), real deployment. You go where the operating problem is and ship production code to real users, not slide decks that sit in a drive.

• Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Embedded is not staff-augmented.

• Autonomous. You own the work from framing through to production, visible to clients and founders. You own the method; nobody hands you a ticket.

• Your experience stays portable. Every engagement is a new problem, often in a new industry, so your skills compound instead of narrowing to one product. No legacy-maintenance grind, not a single stack.

• Craft & growth — build beside senior FDEs on a Claude-certified team; a real platform (talks, OSS) to grow your name.

• We give you a stage: Claude certification, conference talks, open-source contributions, published work under your own name.

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.