Job Type
Full-Time Employee
Note: Roles are posted at the lowest level of a band; however, employees should search across all levels of the band to identify all opportunities. Employees hired on banded positions (e.g., R1–R2, R4–R5) transfer at their current level, despite the level indicated on the job posting.
Lilly’s Purpose
At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our 42,000+ employees work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease and give back to our communities. We give our best effort to our work and we put people first.
Come build advanced software capabilities to accelerate our digital transformation and support Lilly’s evolution to be the leader in Pharma-tech!
Technical Lead Architect — GSS Tech
GSS Tech builds the platforms that power clinical trial statistics, from specifications through validated execution to regulatory submission and drives Statistics Innovation through AI and automation. We operate with an enterprise platform and product mindset and own the full software lifecycle: ideation, build, QA, deployment and monitoring.
We are seeking a Technical Lead Architect to set the technical direction for GSS and to build it. You will transform manual, siloed statistical workflows (for example specification, programming, QC, TLF generation and submission packaging) into intelligent, agentic processes that run in validated, GxP-compliant environments.
This is a technical leadership role that stays hands-on: roughly 40% building and 60% architecture, strategy and leadership. What makes this role senior is the scope and reach of what you design and build. Your reference implementations and production systems become the reference architectures and platform standards that GSS and the wider Tech@Lilly community adopt and your code reviews and pairing are how you grow engineers and emerging technical leads. This is an individual-contributor technical leadership role with no direct reports.
Core Responsibilities
Define the target-state architecture, AI and agentic strategy and roadmap for GSS, including where automation should replace manual steps and turn business priorities into a prioritized investment plan.
Establish reusable reference architectures, secure and compliant patterns and engineering standards through shipped implementations; lead architecture reviews, evaluate emerging technologies and act as the technical authority for architecture decisions, in partnership with enterprise architecture, security and platform teams.
Own technical delivery from scoping through release, managing risks, dependencies and timelines and oversee vendor and partner contributions for quality, security and standards.
Partner with biostatistics, statistical programming, SDN&A and product leaders to align priorities and communicate decisions, trade-offs and delivery status to technical and senior non-technical audiences.
Coach engineers and emerging technical leads through code reviews, pairing and architecture spikes and represent GSS in enterprise architecture forums.
Automate clinical statistics workflows from statistical analysis plan (SAP) to submission, including specifications, ADaM and TFL (tables, figures and listings) programming in R and SAS, QC and CDISC deliverables (SDTM, ADaM, define.xml), using AI agents with statisticians and programmers reviewing results.
Architect the platform where statisticians and programmers work: reproducible, version-controlled, containerized R and SAS environments, with end-to-end lineage from specifications to outputs.
Build cloud-native applications and APIs in Python, Node.js, React and PostgreSQL, including interfaces for statisticians and programmers to specify, review and run analyses.
Design and deliver production GenAI and multi-agent systems and RAG pipelines (for example, LangGraph, AutoGen, MCP, A2A), with human-in-the-loop checkpoints, evaluation and observability.
Deliver on AWS or Azure with CI/CD, monitoring and incident response and set engineering practices for testing, reliability and security.
Use AI tools such as GitHub Copilot and Claude Code to speed up prototyping, testing and debugging and show the team how.
Build validation-ready systems aligned to GxP and 21 CFR Part 11, with audit trails, qualified environments, independent verification (double programming) and guardrails, confidence scoring and explainability for AI agents, working with Quality and computer system validation (CSV) teams on validation strategy.
Required Skills and Expertise
Bachelor’s degree in Computer Science, Software Engineering, or a related technical field (Master’s preferred); 10+ years of software engineering experience, including 4+ years leading technical delivery or architecture for production systems.
Track record of defining architecture direction and technology roadmaps, with production implementations adopted as reference patterns or platform standards.
2+ years building production GenAI or LLM solutions, including agentic patterns (tool use, planning, multi-agent orchestration), at least one agent framework (for example, LangGraph, AutoGen, CrewAI) and working knowledge of MCP and A2A.
Strong expertise across the LLM stack and RAG: prompt and context engineering, function calling, structured outputs, embeddings, vector databases (for example, pgvector), hybrid search and rigorous evaluation of agent performance.
Strong Python, with working knowledge of Node.js (JavaScript/TypeScript), React and PostgreSQL, including schema design and query optimization.
Experience building MLOps and data pipelines on AWS or Azure with CI/CD, model versioning and monitoring, plus Docker, Kubernetes, microservices and event-driven and distributed systems.
Experience with API and integration design, automated testing and security fundamentals (authentication, authorization, secrets management).
Working knowledge of R and SAS and of clinical trial statistical programming workflows, including statistical analysis plans, mock shells, SDTM and ADaM datasets, TFL generation, define.xml and CDISC standards.
Understanding of responsible AI (hallucination mitigation, guardrail design, explainability) and active knowledge of the latest GenAI and agentic AI developments, with an appetite for rapid experimentation.
Track record of coaching engineers through code reviews, pairing and architecture spikes and of influencing technical decisions across multiple teams through shipped work.
Ability to lead through ambiguity, influence senior leaders and non-technical partners and deliver complex programs on time.
Preferred Skills
Experience in pharma, life sciences, or other regulated, validated environments (GxP, 21 CFR Part 11, CSV), including validation and audit-readiness practices.
Familiarity with CDISC standards, clinical trial data flows and regulatory submission processes, including eCTD and analysis data reviewer’s guides.
Familiarity with statistical methods commonly used in clinical trials (for example, survival analysis and mixed models for repeated measures).
Experience with open-source R ecosystems for pharma (for example, tidyverse and pharmaverse) and with Shiny for interactive review of outputs.
Experience with agent design patterns (for example, ReAct, plan-and-execute), agent observability and evaluation frameworks.
Exposure to Databricks or similar data platforms, NoSQL databases and platform engineering.
Experience with SAFe or product-oriented delivery models, including PI planning.
Why Join Us?
This role offers an opportunity to shape how clinical trial statistics is delivered at Lilly. You will work at the intersection of statistics, AI and software engineering in an autonomous team that moves fast, owns the full software lifecycle and partners directly with biostatistics, statistical programming and product leaders. You will set technical direction, build reference implementations that other teams adopt and grow the engineers around you, with visibility to senior leadership and a direct line from your work to faster, validated delivery of trial results. If you want to apply agentic AI where it matters most, in regulated, high-stakes science, this is that role.
Lilly is an equal opportunity employer. Lilly does not discriminate on the basis of age, race, colour, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability, or any other legally protected status. Note: When applying internally, your current supervisor will be notified. We encourage employees to discuss the opportunity with their supervisor prior to applying. #WeAreLilly
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
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