About the job
Flagship Pioneering is building the infrastructure and engineering foundation to make AI a force multiplier across the company. This role sits within IT's Digital Platforms team and operates at the intersection of AI infrastructure, automation engineering, and enterprise use case delivery. You'll work directly with the Enterprise AI team and Digital Platforms to productionize AI capabilities at scale, including MCP builds and integrations, agentic tooling, and cross-functional automation pipelines.
Responsibilities
Design, build, and deploy AI use cases across Flagship business functions, including finance, legal, HR, research, and operations
Maintain AI infrastructure and automation platforms: MCP server builds and integrations, agentic frameworks, LLM orchestration, and low-code/no-code tooling (e.g., Zapier, Workato)
Partner with the Enterprise AI Lead to scope and accelerate the AI use case portfolio, moving requests from triage to production
Build and maintain integrations between AI tools and enterprise systems (Coupa, NetSuite, Slack, M365, and others)
Establish MLOps platform to establish deployment, observability and feedback loops for deployed AI workflows: usage monitoring, output quality tracking, and prompt iteration cycles
Support evaluation and implementation of AI-enabled SaaS tools, including proof-of-concept builds and vendor assessments
Contribute to AI governance infrastructure: usage monitoring, ZDR (Zero Data Retention) compliance checks, sandbox governance, and documentation
Collaborate with Information Security on AI security posture, including data exposure risk, agentic workflow guardrails, and shadow AI detection
Qualifications
Minimum
At least 5 years of technical delivery experience
At least 4 years of software (python preferred) and automation engineering experience, with experience building and shipping LLM-based systems to production
At least 2 years' experience with cloud first architectures (AWS preferred)
At least 2 years' experience building and launching applications and solutions using standard DevOps and MLOps tools.
Hands-on development experience with LLM APIs (Anthropic, OpenAI, or similar) including prompt engineering, tool use, and multi-step agentic workflows
Building experience with MCP and other agentic tool frameworks
Familiarity with maintaining RAG (Retrieval Augmented Generation) architectures, vector databases, and document ingestion pipelines
Working knowledge of enterprise systems including ERP (Enterprise Resource Planning), HRIS (Human Resource Information Systems), and experience with enterprise automation platforms (Zapier, Workato, Make, or equivalent)
Ability to build integrations across SaaS systems using APIs, webhooks, and event-driven architecture
Strong judgment about when to build vs. buy, and how to scope an MVP vs. a production system
Able to identify high-leverage automation opportunities independently and push back on low-impact requests with clear reasoning
Clear communicator who can work directly with non-technical business stakeholders to translate requirements into scoped deliverables
Preferred
Background in life sciences, biotech, or research-adjacent environments
Experience building function alongside delivery in a fast-moving, high-accountability environment
Direct experience with Coupa, NetSuite, Workday, UKG, or similar ERP/HCM platforms