Director – Cloud Platforms, Agent Infrastructure

Role Overview

• Lead the design and operation of Data Foundry’s cloud-native infrastructure (AWS, Azure, and/or GCP)
• Partner closely with the Frontier AI group to build agent-ready infrastructure
• Ensure Architecture4Insight serves as the enabling technical foundation across all Data Foundry pillars
• Design and implement workflow orchestration systems (Prefect, Airflow, Nextflow, WDL)
• Build data access and integration layers providing unified interfaces to diverse data sources
• Lead platform engineering to build shared services, CI/CD automation, API gateways, and microservices architectures
• Collaborate with Tech@Lilly Product Engineering to define pathways for transitioning prototypes to enterprise-managed production systems
• Build, mentor, and help develop a high-performing platform engineering team
• Develop a multi-year roadmap for cloud platforms and infrastructure aligned with Data Foundry strategy.

Requirements

• MS/Ph.D. in Computer Science, Bioinformatics, Computational Biology, or related field, OR M.S. with equivalent experience in platform engineering and scientific software
• 6+ years of experience in cloud platform architecture, scientific software engineering, or research informatics, with at least 3 years in pharmaceutical, biotechnology, or life sciences industry
• Proven track record leading platform engineering or infrastructure teams (6–10+ professionals) delivering production systems
• Deep expertise in cloud-native architecture on AWS, Azure, or GCP including infrastructure-as-code, containerization, orchestration, and security
• Strong software engineering skills with experience in multiple programming languages and modern development practices
• Experience building APIs, microservices, and integration layers for complex scientific or technical systems
• Demonstrated ability to translate scientific requirements into technical architecture and scalable platform solutions
• Excellent communication skills with ability to explain technical concepts to scientists, collaborate with IT organizations, and influence stakeholders
• Experience with AI agent infrastructure, autonomous system platforms, or building APIs that AI/ML systems invoke programmatically
• Hands-on experience with Model Context Protocol (MCP) servers, LangChain, or similar frameworks for AI agent tool integration
• Deep understanding of workflow orchestration tools (Nextflow, Prefect, Airflow, WDL, Snakemake) and experience building automated scientific pipelines
• Experience with genomics, proteomics, or bioinformatics platforms and understanding of scientific data characteristics
• Familiarity with LIMS, ELN systems, and laboratory automation data integration patterns
• Track record of founding or building platforms from ground up, not just maintaining existing systems
• Experience with data governance, semantic modeling, ontologies, and metadata frameworks in scientific contexts
• Strong mentorship capabilities with passion for developing engineering talent and building collaborative teams
• Entrepreneurial mindset with ability to operate in ambiguous, fast-paced research environments.

Tech Stack

• Airflow
• AWS
• Azure
• Cloud
• Google Cloud Platform
• Microservices

Benefits

• Eligibility to participate in a company-sponsored 401(k)
• Pension
• Vacation benefits
• Eligibility for medical, dental, vision and prescription drug benefits
• Flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts)
• Life insurance and death benefits
• Certain time off and leave of absence benefits
• Well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities)