Technical Lead - Forward Deployed Engineering

The Technical Delivery Lead for Forward Deployed Engineering (FDE) leads a small, high-velocity engineering team that embeds directly with frontline business partners across product development, manufacturing, Quality and Finance. Working side by side with scientists, operators, quality professionals and finance teams at our sites, this leader identifies critical business problems, then uses data science, AI and modern software engineering to design and ship working prototypes in weeks, not quarters.
This is more than an individual contributor engineering role. The successful candidate is accountable for the technical direction, quality and delivery pace of FDE engagements, leads and develops the engineers on each engagement, and is a hands-on builder who sets the technical bar for the team.
Responsibilities:
Technical delivery leadership
Serve as technical delivery lead for a portfolio of fast-paced FDE engagements, owning scope, architecture, technical risk, timelines, and outcomes from problem framing through prototype and handoff.
Lead, coach, and assign work to a team of forward deployed engineers, data scientists, and partner resources; set engineering standards, review designs and code, and build team capability.
Run short, iterative delivery cycles (e.g., discovery sprints, weekly demos) that move rapidly from hypothesis to a working solution in users’ hands.
Make clear build/buy/scale decisions and define the path from prototype to production with BTS platform, product, and support teams.
Frontline partnership
Travel to AbbVie sites to work directly with frontline employees—on the manufacturing floor, in labs, in Quality and in Finance—to observe workflows, understand pain points and co-design solutions.
Translate ambiguous operational and financial problems into well-defined technical problems with measurable success criteria (e.g., cycle time, yield, right-first-time, deviation reduction, close timeliness).
Build trusted relationships with site leaders and business stakeholders; communicate progress, trade-offs, and results clearly to both technical and non-technical audiences, including senior leadership.
Hands-on solution development
Rapidly develop prototypes using data science, machine learning, generative AI / LLM and agentic tools, analytics, and application development frameworks.
Integrate with enterprise and operational data sources such as MES, LIMS, QMS, ERP (e.g., SAP), historians, and data lake / cloud platforms.
Apply AI-assisted development practices to accelerate delivery while maintaining code quality, security, and maintainability.
Ensure solutions are designed with appropriate data integrity, privacy, cybersecurity, and responsible AI considerations, and engage Quality/CSV partners early where GxP impact exists.
Scale and impact
Capture reusable patterns, components and playbooks so successful solutions can be replicated across sites and functions.
Quantify and report business value delivered by FDE engagements; help shape the FDE engagement model and pipeline with BTS Operations & Finance leadership.
Required:
Bachelor’s Degree in Computer Science, Engineering, Data Science, a physical/life science, or related field with 7 years of relevant experience; Master’s Degree with 6 years of experience; or PhD with 2 years of experience.
Demonstrated experience delivering data, analytics, AI, or software solutions in the life sciences industry (pharmaceutical, biotech or medical device) across one or more of: product development, manufacturing, Quality or Finance.
Proven track record leading technical teams—setting direction, mentoring engineers and accountable for delivery of multiple concurrent projects.
Strong hands-on engineering skills in Python and SQL, with experience building and deploying ML/AI solutions, including generative AI / LLM applications.
Experience with cloud data and compute platforms (e.g., AWS, Azure, Databricks, Snowflake) and modern software practices (Git, CI/CD, APIs, containerization).
Experience working in rapid, iterative delivery environments—taking ambiguous problems to working prototypes on short timelines.
Working knowledge of regulated environments (GxP, data integrity, computerized system validation) and how they shape solution design.
Excellent communication and stakeholder management skills; comfortable working directly with frontline staff and presenting to senior leaders.
Willingness and ability to travel to sites up to 20% of the time.
Preferred:
Prior forward deployed, solutions engineering, technical consulting, or internal innovation “skunkworks” team experience.
Familiarity with manufacturing and quality systems and data (MES, LIMS, QMS, historians such as OSIsoft PI) and/or finance systems (SAP, planning and close tools).
Experience with agentic AI frameworks, retrieval-augmented generation, computer vision, or optimization/simulation methods.
Experience with full-stack or low-code application development for rapid user-facing tools (e.g., React, Streamlit, Power Apps).
Experience moving prototypes to scaled, supported production solutions in partnership with platform and product teams.

Skills
Python, React, Git, AWS, Azure, CI/CD, SQL, Snowflake, Databricks, Machine Learning

Employment type
Full-time

Work arrangement
Hybrid