Forward Deployed AI Engineer

Transformworks•New York, NY

3d•$165,000 - $300,000•Hybrid

About The Position

Transformworks is an AI implementation partner to the world’s most ambitious investors and operators. We work with companies in critical, operationally complex industries, including healthcare, education, and financial services. Our work includes: Helping an education organization scale the development of high-quality curriculum across thousands of schools in the U.S. Automating paperwork and documentation for a healthcare services company supporting more than 2 million patients, freeing its teams to spend more time helping the people they serve We are profitable, growing quickly, and intentionally lean. We believe AI has fundamentally changed what one exceptional engineer with strong business judgment can accomplish, so we keep teams small, give people real ownership, and reward them based on the value they create. As a Forward Deployed AI Engineer, you will work directly with client executives, operators, and technical teams to turn high-value business problems into production AI systems. You will own the full journey: understanding the workflow, defining what should be built, designing the technical approach, shipping the system, and improving it until it delivers measurable results. This is a hands-on engineering role. You will write production code, make architecture decisions, and work directly with users. You will also need the judgment to prioritize the right problem, communicate clearly with clients, and keep an engagement moving through ambiguity. We are not looking for someone who only wants to build prototypes or work from detailed specifications. We are looking for someone who wants to figure out what matters and own the outcome. As a Forward Deployed AI Engineer, you will work directly with client executives, operators, and technical teams to turn high-value business problems into production AI systems. You will own the full journey: understanding the workflow, determining what should be built, designing the technical approach, shipping the system, and improving it until it delivers measurable results. This is a hands-on engineering role for someone who wants to figure out what matters, not simply build from a detailed specification. Build and deploy AI agents, workflow automations, data pipelines, integrations, and internal applications Work directly with clients to understand their operations, systems, and business objectives Own technical workstreams from discovery through deployment, adoption, and iteration Build evaluation, monitoring, and human-review systems that make AI reliable in production Communicate technical decisions, progress, and tradeoffs to engineers, operators, and executives Turn lessons from client engagements into reusable tools and engineering standards You will work directly alongside the founders and senior engineers from day one. As you develop, you will take ownership of larger technical workstreams, lead client engagements, manage teams, and help shape how Transformworks delivers AI at scale. At a small company growing quickly, that progression can happen much faster than it would inside a traditional consulting firm or engineering organization.

Requirements

2+ years of experience building software or applied AI systems
Strong Python fundamentals and comfort working across APIs, databases, and cloud infrastructure
Hands-on experience building with LLMs through professional work or substantive independent projects
Evidence that you have shipped something real and can explain how it evolved after reaching users
Strong product and business judgment
Clear communication and comfort working directly with clients
A high degree of ownership and the ability to make progress through ambiguity

Nice To Haves

Experience with agentic workflows, RAG, evaluation systems, TypeScript, React, or regulated industries is helpful but not required.

Responsibilities

Build and deploy AI agents, workflow automations, data pipelines, integrations, and internal applications
Work directly with clients to understand their operations, systems, and business objectives
Own technical workstreams from discovery through deployment, adoption, and iteration
Build evaluation, monitoring, and human-review systems that make AI reliable in production
Communicate technical decisions, progress, and tradeoffs to engineers, operators, and executives
Turn lessons from client engagements into reusable tools and engineering standards