Job Description

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 employees around the world 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 through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

We are a global
healthcare leader headquartered in Indianapolis, Indiana. Lilly India Commercial function BI&A (Business Insights & Analytics) team supports business decisions for
the commercial and marketing functions in the US and ex-US affiliates. The team comprises 100+
members across data management, analytics, data science, business, and commercial operations. Role Summary
Lilly India Commercial function BI&A is hiring an Associate Director to lead AI Engineering & Operations,
responsible for building and running production-grade AI systems across the full AI lifecycle—spanning
traditional ML engineering/MLOps and agentic AI systems (LLM/agent workflows, tool use,
orchestration). The leader will partner closely with onshore BI&A stakeholders and Lilly IT/platform teams
to deliver scalable, reliable, secure, and compliant AI capabilities that drive measurable business impact. Key Responsibilities
People & Delivery Leadership
• Lead, coach, and grow a high-performing team of ML/AI engineers and operations talent; set
clear expectations on engineering quality, reliability, and productivity. • Establish best practices for execution (planning, project management, technical design reviews,
documentation, and continuous improvement). • Collaborate with data scientists, software engineers, and infrastructure teams to design optimal
end-to-end pipelines and AI product delivery. AI Engineering Platforms & Reusable Capabilities
• Build and operationalize reusable capabilities that enable teams to develop and deploy AI tools,
assistants, and agents at scale, including standardized templates/SDKs, integration patterns, and
deployment readiness. • Enable robust RAG and agentic workflows: ingestion, retrieval, orchestration patterns, tool
calling, and integration with enterprise systems. • Establish lifecycle discipline for AI systems: versioning/registry, automated evaluations, safe
rollout/rollback, and continuous improvement loops
AIOps, Observability & Operational Excellence
• Implement end-to-end observability for AI services (pipelines, agents, and applications):
monitoring, tracing, cost/usage visibility, and operational dashboards. • Drive incident and problem management practices (triage, postmortems, prevention
automation) to improve reliability and reduce operational toil. • Optimize for latency, quality, and cost trade-offs; define and track operational metrics aligned to
business outcomes. Governance, Security & Compliance
• Ensure secure, compliant AI delivery with enterprise authentication, audit trails, and “security-
by-design” practices (including policy-based enforcement where required). • Implement guardrails and responsible AI practices suitable for regulated environments, in
partnership with risk/security stakeholders. Strategic Growth & Thought Leadership
• Identify capability gaps and opportunities; build a roadmap to expand BI&A’s AI engineering
outcomes and scale adoption. • Provide thought leadership and run PoCs to modernize AI operations across cloud/on-prem
environments, CI/CD automation, and multi-team delivery. Minimum Qualifications (Required)
• 10+ years relevant experience across software/ML engineering, MLOps, or AI operations; 3+
years leading teams and delivering across multiple stakeholders. • Strong hands-on foundation in cloud-native engineering and DevOps/MLOps practices
(containers, orchestration, CI/CD, automated testing, release discipline). • Experience operationalizing end-to-end ML solutions (training/serving/monitoring) and modern
GenAI/agent workflows (evaluation, monitoring, lifecycle management). • Proven ability to build scalable operating models, enforce quality standards, and communicate
trade-offs with senior stakeholders. • Strong communication, collaboration, and people leadership skills
Preferred Qualifications (Nice to Have)
• Experience with LLM/agent observability practices (tracing across prompt → retrieval/tool calls
→ response) and cost controls for GenAI systems. • Experience with policy-as-code / compliance-ready audit logging patterns in enterprise
environments. • Experience in regulated domains (healthcare/life sciences/finance) operating under audit and
compliance constraints. Education
• Master’s degree in Computer Science/Engineering/Mathematics or related field

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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