AI Engineer

Translucent•New York City, NY

4d•Hybrid

About The Position

We're looking for an AI Engineer to help build the agentic platform at the core of Translucent: the AI financial platform transforming how healthcare organizations make business decisions. You'll work hands-on across R&D and platform engineering — improving the underlying agent capabilities every team builds on, rather than configuring agents for a single customer. You'll standardize the tool surfaces new capabilities plug into, make the agent platform ready to integrate across products, and own the evals, context, and harness engineering that make it reliable enough for healthcare finance. You'll match the right agentic architecture to each use case, turn core capabilities into an ecosystem others build on, and own quality end-to-end. If you are energized by fast-paced environments, love sweating the details of production AI systems, partnering closely with product and design, and seeing your work in customers' hands quickly, you'll feel at home here.

Requirements

3+ years of software engineering experience, with meaningful production work in Python
Direct experience shipping LLM-powered or agentic systems in production — not just prototypes. You know where models fail and how to make them reliable
Hands-on experience with at least one modern agent framework (LangGraph, Google ADK, LlamaIndex, Claude Agent SDK, or equivalent), and a clear point of view on what to use vs. build
Production evals and benchmarking — you've built eval harnesses and benchmarks that gate real releases, not one-off spot checks
Context engineering — grounding agents through retrieval, context layers, and knowledge transfer so outputs match a specific org or user
Comfort with the data and retrieval layer — SQL, BigQuery or a comparable warehouse, embeddings, and vector search
A bias toward shipping — you take an ambiguous problem to a working V1 fast, then iterate
Plus deep, demonstrable expertise in at least one (ideally two) of the following: Tool-surface and connector platform engineering — standardized tool/skill contracts (e.g., MCP) and connector ecosystems that scale without breaking
Harness and loop engineering — agent control loops, orchestration, and inference harnesses; right-sizing agent architecture per use case and keeping it reliable at scale
Open-source and in-house model fine-tuning — fine-tuning open models and benchmarking them against frontier baselines
Production context-layer engineering — systems that capture business rules and preferences and feed them to agents reliably

Nice To Haves

Experience with healthcare finance, accounting, or other structured financial data — or genuine curiosity about it
Applied ML or model-evaluation research background
Open-source contributions to agent or LLM tooling
Experience designing tool-use APIs or developer-facing AI products
Familiarity with our stack: Vertex AI (Gemini, Claude on Vertex), GenKit, MCP, BigQuery

Responsibilities

Standardize tool and skill surfaces — define the contracts (MCP-style tool, connector, and skill interfaces) that let us add new capabilities continuously without destabilizing the platform as it grows
Make the agent platform integration-ready — build the connective tissue so agents, tools, context, and data compose cleanly across products, and match the right agentic architecture to each use case
Own evals and benchmarks — build production-grade eval harnesses, replay, and benchmarks for agentic AI, and gate releases on them; in healthcare finance, accuracy is non-negotiable
Lead context and harness engineering — establish best practices for grounding agents in each customer's business rules and data, and for the control loops that keep outputs reliable
Fine-tune and evaluate models — fine-tune in-house and open-source models, benchmark them against frontier baselines, and make the build-vs-buy calls on model, framework, and infra
Turn capabilities into an ecosystem — build reusable core capabilities that translate across features and products, and ship them end-to-end with product and design