Forward Deployed Engineer (BioPharma/Lifescience)

Condor Software•San Francisco, CA

65d•Hybrid

About The Position

Condor is building the financial intelligence layer for clinical development, connecting clinical operations, vendor activity, and financial signals into a single, real-time intelligence layer. This role is for a Forward Deployed Engineer who will be embedded directly with biopharma customers to design and deploy high-impact, AI-powered solutions. This is an active engineering role where you will contribute to the core codebase by opening PRs to build production-grade capabilities. You will act as the technical authority, driving rapid execution and feeding insights back into the platform's architecture and product roadmap. It's a highly autonomous opportunity for engineers who thrive in high-stakes environments and want to shape the future of biopharma infrastructure.

Requirements

Has held a forward-deployed, founding-engineer, or similar zero-to-one customer-facing role, and turned messy real-world requirements into shipped software.
4–10 years of software engineering experience with real depth — you’ve built and owned end-to-end production systems, not just features inside a large existing one.
Builds end-to-end systems quickly with AI. You use LLMs and agent frameworks (function calling / tool use, RAG, evals) to go from problem to working system fast, and you own their reliability, evaluation, and cost.
Translates customer needs into core products. A track record of taking a customer problem and implementing the solution directly in a shared core codebase.
Deep software engineering fundamentals. Strong proficiency in Python and Django; solid data modeling and SQL on PostgreSQL; comfort building on AWS (Bedrock, ECS/Fargate, Lambda).
Strong communicator. At ease with both technical and non-technical stakeholders, and credible in front of a customer.
High ownership. Able to operate independently in a fast-changing, ambiguous environment and drive a deployment to completion.

Nice To Haves

Background from companies known for the FDE or zero-to-one model — Palantir, Anduril, Cursor, Cognition, or similar.
Experience with vector search and retrieval (Pinecone, pgvector) and graph/relationship stores (Neo4j).
Exposure to clinical operations, biopharma R&D, financial systems, or other regulated, high-correctness data domains — or experience integrating with clinical and financial systems (ERP, CTMS, EDC, procurement, vendor feeds).
Experience building evaluation and observability for LLM applications.
React for customer-facing UI is a plus.

Responsibilities

Embed directly with biopharma customers to understand their workflows, constraints, and definition of success across both finance (accruals, forecasting, reconciliation) and clinical operations (vendor activity, study execution, operational data).
Uncover and validate new use cases in the field to the granular details, including clinical operations problems adjacent to finance and clinical operations and turn the most valuable ones into product.
Design, build, and deploy AI-driven solutions to real operational problems — fast, in days rather than quarters.
Turn ambiguous customer requirements into technical architecture and ship them into Condor’s core platform, not one-off prototypes.
Build and maintain production systems: Django services and APIs, agent workflows on AWS Bedrock, data integrations, monitoring, and feedback loops.
Build customer-facing systems end-to-end—from UI to backend to data to AI—to surface a capability fully.
Own deployments end-to-end, from initial scoping through launch and iteration.
Operate in high-stakes environments where reliability, speed, accuracy and judgment matter — this is financial data customers close their books on.
Identify patterns across deployments and codify field work back into core product and platform capability.
Partner closely with Product and Engineering to influence roadmap, abstractions, and long-term system design.