Director - Cloud Platforms & Agent Infrastructure

Role Summary

The Senior Director, Cloud Platforms & Agent Infrastructure will lead technical architecture and platform engineering for Data Foundry's cloud-native infrastructure. Reporting to the Head of Architecture4Insight, you will build scalable, secure, and agent-ready systems that enable both human scientists and autonomous AI agents to accelerate molecule discovery. Location: San Diego, CA; San Francisco, CA; Louisville, CO; Indianapolis, IN; Boston, MA.

Responsibilities

• Lead the design and operation of Data Foundry’s cloud-native infrastructure (AWS, Azure, and/or GCP), including infrastructure-as-code, containerization, orchestration, and self-service platforms that empower discovery scientists to deploy tools and run analyses at scale.
• Partner closely with the Frontier AI group to build agent-ready infrastructure—including APIs with structured error handling, versioning, and audit trails; Model Context Protocol (MCP) servers; and real-time data streaming architectures—that enable autonomous AI agents to access data, invoke analytical methods, and control laboratory systems.
• Ensure Architecture4Insight serves as the enabling technical foundation across all Data Foundry pillars: deploying Methods4Insight’s analytical models as production APIs, integrating Scale4Insight’s real-time instrument data streams, and embedding Preparedness4Insight’s governance and metadata standards into platform design.
• Design and implement workflow orchestration systems (Prefect, Airflow, Nextflow, WDL) that automate data pipelines, enable closed-loop experimentation, and provide reusable workflow templates for scientists.
• Build data access and integration layers providing unified interfaces to diverse data sources (LIMS, ELNs, instruments, databases), with caching, indexing, and query optimization for interactive analytics and agent queries.
• Lead platform engineering to build shared services, CI/CD automation, API gateways, and microservices architectures used across Data Foundry, establishing software engineering best practices and modern development standards.
• Collaborate with Tech@Lilly Product Engineering to define pathways for transitioning prototypes to enterprise-managed production systems, establish SLAs, and represent Data Foundry in enterprise architecture forums.
• Build, mentor, and help develop a high-performing platform engineering team of architects, software engineers, and DevOps specialists, fostering a culture of technical excellence and continuous learning.
• Develop a multi-year roadmap for cloud platforms and infrastructure aligned with Data Foundry strategy, monitoring emerging technologies and establishing KPIs for platform performance, cost efficiency, and scientist satisfaction.

Qualifications

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

Additional Requirements

• Travel: Approximately 15–20% travel to collaborate with teams across multiple Lilly sites and occasional external conferences.