As a Systems & Reliability Engineer at Peer AI, you will bridge the gap between development and production, building sustainable speed through observable and reversible releases. You’ll own the path from merge to production, automate operational toil using AI, and evolve the platform toward GxP compliance for high-stakes regulatory environments.
Systems & Reliability Engineer at Peer AI
Peer AI is transforming the $23B regulatory submission market for pharma, and they’re looking for a Systems & Reliability Engineer to build the foundation for sustainable, high-velocity shipping. In this role, you won't just manage infrastructure—you'll build an AI-native platform that uses LLMs to automate incident response and root-cause analysis. With top-tier pharma customers already on board and deep venture backing, Peer AI offers a chance to work on high-stakes systems that directly accelerate life-saving clinical research. Join a mission-driven team where engineering speed meets rigorous reliability.
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Location
Bay Area, United States
Compensation
Not Disclosed
Company
Peer AI
Role overview
Peer AI is an AI-native platform focused on transforming regulatory submissions and documentation for life sciences and biopharma companies. It provides purpose-built, domain-specific AI agents and an intuitive, AI-powered user interface to automate and accelerate the drafting of complex regulatory documents such as clinical study reports (CSR), safety narratives, investigational new drug (IND) applications, biologics license applications (BLAs), protocols, investigator’s brochures (IBs), and plain language summaries, while keeping medical writers in full control at critical decision points.[1][5][8][15] The platform is positioned as an agentic AI solution for regulatory documentation, designed to reduce drafting time, provide workflow visibility and control across programs and teams, and offer predictive regulatory intelligence that helps teams anticipate reviewer queries and streamline submission workflows.[1][5][8][14][15] Peer AI’s mission is to transform drug development with AI-powered intelligence by connecting documentation, data, and decision-making so treatments can reach patients faster, drawing on deep expertise in life sciences, data protection and privacy, and generative AI.[3][14] The company serves pharmaceutical, biotech, and contract research organizations (CROs) worldwide and is backed by leading venture investors, having raised over $12 million in funding to expand its regulatory AI platform.[5][8][15]
What you will do
- Own and evolve the end-to-end deployment pipeline, ensuring releases are observable, reversible, and supported by automated safety signals and rollout controls.
- Establish a lightweight, effective incident response and on-call process that turns recurring operational work into automated software systems and predictable escalation paths.
- Partner with Quality and Security teams to implement GxP-compliant change control, release evidence, and production monitoring for highly regulated pharmaceutical environments.
Who this is a fit for
- Strong software engineering fundamentals with the ability to solve complex problems across both application code and distributed cloud-native infrastructure.
- Hands-on experience managing AWS environments using containers, infrastructure automation, and modern observability tools like CloudWatch, ECS/Fargate, and PostgreSQL.
- A deep-seated bias toward removing toil through software and a clear judgment on where process adds safety versus where it creates unnecessary bureaucracy.
Why this role is remarkable
- Work at the intersection of AI and life sciences, directly accelerating the delivery of life-saving medical discoveries to patients who need them most.
- Join a high-growth, venture-backed company that is already live with major pharmaceutical customers in a massive and critical $23B addressable market.
- Shape an AI-native engineering culture where you will use LLMs and agents to automate incident triage, root-cause investigation, and production operations.
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