Portfolio Manager, Government Partnerships (DARPA & ARPA-H)
Lila Sciences · Cambridge, MA USA · One Charles Park, Cambridge, MA
CHECKED 15H AGO
Bio & Science AIonsitesenior$168k–$272k
At a glance
Highlights
- Own DARPA and ARPA-H portfolio end-to-end for AI-driven science.
- Turn autonomous-lab capabilities into pilots, CRADAs and major procurements.
- Build trusted agency posture shaping mission-critical science engagements.
What they offer
- Competitive base compensation with bonus potential and generous early-stage equity
- Medical, dental, and vision coverage
- Employer-paid life and disability insurance
- Flexible time off with generous company holidays
- Paid parental leave
- Educational assistance program
- Commuter benefits and company subsidized lunch program
Ideal candidate
A mission-driven builder with deep public-science networks who loves translating complex science into compelling narratives and forging durable agency partnerships for breakthrough discovery.
Requirements
- 10+ years of experience in federal or international government capture, business development, or partnerships with track record of winning major awards
- Working fluency in at least one major public-science ecosystem, with strong preference for DARPA and/or ARPA-H
- Demonstrated ability to manage end-to-end capture from identification through award and execution handoff
- Experience translating complex science and AI into clear narratives for senior and policy-facing audiences
- Strong cross-functional leadership partnering with scientists, product, communications, policy, and legal
- Excellent written communication and comfort operating with ambiguity
- Willingness to travel regularly to build required relationships
Lab profile
About Lila Sciences
Building an autonomous science platform where AI, automation, and biology co-evolve for medicine and materials.
What they build
- Autonomous Science Platform
- AI-designed biologics validated in wet-lab
- Electro-optic materials and photonic devices
Known for
- Large-scale automated data generation
- High-throughput protein purification and analytics
- Protein design and BioML modeling
- Robotic orchestration and lab simulation