Your opportunity

Our client is a well-funded, venture-backed AI platform company on a mission to make life-saving drugs accessible and affordable for everyone. They build agentic AI and data infrastructure for the world's largest pharmaceutical, biologics, and specialty chemical manufacturers, helping them increase production efficiency, reduce costs, and minimize waste. Their thesis is that the bottleneck preventing therapies from reaching patients at scale is not scientific, it's operational: manual, fragmented, paper-heavy processes across regulated manufacturing. The faster that bottleneck clears, the faster medicine gets to the people who need it.

As their founding forward deployed engineer, you'll be the first hire on a new team sitting at the intersection of the product and enterprise customers. You’ll split time between core product engineering and building within their customers’ environments. Success in this role means understanding the customers’ data environments, deploying and configuring the platform, building custom integrations and workflows, and ensuring the product delivers real, measurable value. This is not a sales engineering or solutions consulting role. You will write production code in the customer's environment, on their data with an expectation that ~80% of what you build merges back into the main platform. You will also heavily influence the product roadmap by serving as a critical feedback loop between customers and the internal product and engineering teams.

The product surface spans an operational data platform, an AI-powered document intelligence layer distributed natively on Snowflake, a raw material variability and genealogy analytics product, and most recently a GxP-grade AI agent for shop-floor decision-making that integrates with MES, QMS, and LIMS systems to produce traceable, audit-ready insights. The company has collected several awards and accolades, and established strategic global distribution partnerships spanning North America, Europe, the Middle East, and India. Their reference customers include some of the world's largest pharmaceutical and chemical manufacturers.

Our client prioritizes talent density and has built a high-ownership, high-autonomy environment with a track record of fostering accelerated professional development.

Please note that while the overwhelming majority of forward deployed work happens remotely, there is very occasional travel (roughly twice annually) to customer sites across North America and Europe. 

Key responsibilities

• Product engineering: Translate customer needs and pain points into actionable signals for the internal product and engineering teams, and merge the majority of what you build back into the main platform

• End-to-end deployment ownership: Own the platform deployment into enterprise pharma and manufacturing accounts from kickoff through go-live and ongoing stewardship, observability, alerting, and incident response

• Customer-specific integrations and workflow extensions: Build connectors between customer systems and the platform, and adapt the workflow orchestration engine to customer-specific process requirements

• LLM pipeline configuration and tuning: Configure and extend AI-powered document processing pipelines (LLM extraction, RAG, structured output validation) for customer document types against accuracy, latency, and cost acceptance criteria

• Enterprise enablement: Navigate security reviews, SSO integrations, VPC configurations, and GxP/SOC 2/HIPAA compliance requirements alongside customer IT, data engineering, and operations teams

• Customer-facing technical leadership: Represent the company technically in customer meetings, workshops, and executive briefings, and create the technical documentation, runbooks, and integration guides

Tech stack

• Backend: Python (Django, FastAPI, asyncio), TypeScript (Node.js/Fastify)

• Frontend: Typescript (Next.js, Nx monorepo)

• AI/ML: Commercial and open-source LLMs, AWS Textract, PaddleOCR, embeddings / vector search

• Data: Snowflake (Snowpark), PostgreSQL, S3, dbt, pandas

• Job orchestration: BullMQ, Redis

• Infrastructure: AWS (ECS/Fargate, RDS, CloudFront, Lambda), Terraform, Docker

• Observability: OpenTelemetry, Datadog, CloudWatch

Your know-how

• You have 6+ years of experience as a software engineer and have recent experience with field deployments and shipping software inside customer environments

• You are very comfortable with Python, production-grade system design and async patterns

• You have experience shipping LLM-enabled features and products and are familiar with prompt engineering, schema validation and cost/latency optimization

• You have experience deploying and operating AWS (or comparable) infrastructure with Terraform

• You have a fantastic command of English and are equally comfortable presenting to executive stakeholders and pairing with hands-on engineers

• You have a practical handle on security and compliance constraints and considerations (SOC 2, HIPAA, GxP, or similar)

• You are comfortable working with fuzzy problems and have a high sense of ownership over your work 

It's a bonus if

• You have pharmaceutical, biotech, biopharma, or regulated manufacturing domain knowledge or an acute interest in learning about these domains

• You're drawn to mission-driven work and the idea of helping make life-saving therapies more accessible speaks to you directly

• You have experience with document processing, OCR (AWS Textract, PaddleOCR), or production RAG systems

• You have experience helping scale an enterprise B2B venture

Interested in learning more?

Please upload your resume or a .pdf export of your LinkedIn profile using the following "Apply Now" button, or send your resume or LinkedIn profile URL to talent@lutrapartners.com with "Founding Forward Deployed Engineer, Biopharma AI" as the subject line. One of our talent partners will be in contact shortly.