Artificial Intelligence Engineer

About the role

Location: New York City, NY, USA. Hybrid, four days on-site (Monday to Thursday)

Job type: Permanent, full time

Salary: $175,000 to $300,000 base, plus performance bonus and competitive equity

Start: ASAP

Sponsorship: Open to visa transfers (OPT, H1B)

Recruiter: Staffworx Limited

Reference: SWX-889456

Contact: james.kirk@staffworx.co.uk

AI Engineer, Agentic Platform. New York City. $175,000 to $300,000 plus bonus and equity.

Staffworx is retained on an exclusive search for a Series A venture-backed AI company building the financial operating system for US healthcare. The business is around 30 people, headquartered in Manhattan

US healthcare providers account for roughly $2.5 trillion of medical expenditure on margins of two to five per cent, and a meaningful number of provider organisations are at genuine risk of failure. Finance teams are stuck in spreadsheets and disconnected legacy systems. Our client automates that manual data work with agentic AI, so finance leaders can act on current information rather than last month's.

This is a platform role, not a customer configuration role. You will build and harden the agentic layer that every product team builds on top of.

What you will be doing

Defining the MCP-style tool, connector and skill contracts that let new capabilities be added continuously without destabilising the platform

Building the connective tissue so agents, tools, context and data compose cleanly across products

Owning production-grade eval harnesses, replay and benchmarks, and gating releases on them

Leading context and harness engineering, grounding agents in each customer's business rules and data

Fine-tuning in-house and open-source models, benchmarking against frontier baselines and making the build versus buy calls

What we need to see

Five to ten years in AI/ML engineering, primarily Python, with agentic systems shipped and running in production

Real depth in evals, harness engineering, context engineering and tool surfaces, rather than framework-level familiarity

Rigorous machine learning foundations. You should be able to explain model architecture and training from first principles at a whiteboard

Experience building end to end in a startup environment, with clear evidence of independent ownership

BS or MS in Computer Science, Mathematics, Machine Learning, Statistics or a closely related quantitative discipline

Relational data modelling. GCP and Vertex AI are a strong plus, as is experience with the Claude SDK

Excellent written and spoken English. The culture is documentation driven and opinions are solicited in writing

Culture and working pattern

Small, deliberately senior engineering team with a flat, democratic structure and RFC-style decision making. Heavily agentic development process with strong human judgement layered on top. Four days a week in the New York office, Monday to Thursday, with Fridays worked from home. The team is hiring two to three people into this role.

Selection process

Twenty minute introductory call with the Head of Engineering, a two hour take-home machine learning exercise, a one hour remote review of that exercise with two AI engineers, then a single on-site final round in New York covering technical and behavioural interviews, a product conversation and CEO sign-off. Offers follow quickly.