Sr. Engineer, Forward Deployed GenAI
Listed on 2026-06-03
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Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
The Role
As a Forward‑Deployed Engineer at Trinity Life Sciences, you are embedded directly inside biopharma and commercial Life Sciences teams: absorbing their hardest problems, then building working solutions fast. You move from an ambiguous business challenge to running a prototype in days, not quarters. You demo it, iterate live with clients, and make it better. You will write real code, own real deployments, and be accountable for real outcomes.
For example, within a week you might be turning a messy CRM export into a live sales‑rep‑facing AI assistant that surfaces next‑best‑action recommendations, or building a RAG pipeline over 10 years of clinical trial data so a market access team can answer payer questions in seconds instead of days.
- Embed with clients at top biopharma and life sciences organizations — sit with their commercial, medical affairs, and data teams to surface unmet needs and translate them into engineered solutions
- Prototype at speed: stand up GenAI‑powered applications, RAG pipelines, agentic workflows, and data integrations fast enough to make a client's jaw drop within two weeks of receiving their data
- Own delivery end‑to‑end: from the first whiteboard session through production‑ready code, demo, feedback loop, and handoff to product
- Flex between missions: move between active client engagements and product sprint as priorities shift
- Make the model and our products better: document patterns, share playbooks with the cohort, and push field learnings back into the product, including reusable components
You can hold a conversation with a Director of Commercial Operations in the morning and translate that into a deep technical conversation with a software architect in the afternoon.
Specifically, You- Thrive on pace: compressed timelines energize rather than exhaust you; you do your best work when the deadline is real
- Understand before you build: you invest the time to genuinely absorb what a client needs, not what they said they need, before you write a line of code
- Are not married to your own work: you iterate freely, kill your darlings without drama, and treat client feedback as signal rather than criticism
- Are collaborative by default: you pull in teammates, ask for help early, and share credit; you do not disappear into a solo cave for three weeks
- Learn fast in unfamiliar domains: you have cracked new industries, new stacks, or new problem spaces quickly before, and you can do it again
- 5–8 years of professional software engineering experience, with a track record of shipping production‑quality systems
- Strong proficiency in Python and/or Node.js/React.js; fluency with cloud services (Azure, AWS, or GCP)
- Hands‑on experience building or integrating GenAI systems; LLMs, prompt engineering, RAG, agentic architectures, or multi‑modal pipelines
- Real comfort operating in client‑facing environments: you have presented to non‑technical stakeholders and navigated their feedback without losing your footing
- Experience in Life Sciences or Biotech strongly preferred: you understand the commercial model, can talk the language, and understand goals of stakeholders in the industry
- Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience)
- You will be part of a cohort, with direct input on how the team operates
- You will work in pods, never alone on a client; there is always a Solution Lead and domain SME at a client with you
- You will have a dedicated FDE Lead who manages the team, advocates for your needs, and handles prioritization across clients. This is not an afterthought
- You will be onboarded intentionally
- Your work has a direct feedback loop to our products. The best things you build in the field become product features – meaning they will shape the industry
Trinity’s salary bands account for a wide range of factors that are considered in making compensation decisions including but not limited to skill sets and market demand for skills; level of experience and training; specific qualifications, performance, time in role/company, geographic location, and other business and…
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