Full Stack Engineer

You'll work with the founding team, enhancing a working platform with paying customers. You will report directly to the CTO and own significant parts of the platform alongside the founding team. You will make architectural decisions that shape the product for years, work directly with pharma customers on problems that have never had good software solutions, and help build the engineering culture of a company shipping serious software into a highly regulated industry. This is a hands-on, high-ownership role. You will write production code every day and set the bar for what we ship. For the right person, we see a clear path into Head of Engineering as the team grows, with the opportunity to hire, lead, and shape the engineering org.

What You'll Work On Architecting and scaling our AWS infrastructure to support a growing portfolio of trials, while maintaining the security posture pharma IT teams expect (SSO, WAF, SIEM, pen testing) Building robust, flexible data integrations across the fragmented landscape of clinical trial data sources, dictionaries, and standards Designing the infrastructure that makes a hybrid LLM and heuristic system reliable enough for regulated use: evaluation pipelines, reproducibility, audit trails, and guardrails Working directly with customers (data managers, medical monitors, biostatisticians) to understand their workflows and pain points, and translating what you learn into product Partnering on deployments, sandbox environments, and pilot studies Setting technical direction: stack choices, code review standards, testing discipline, deployment workflows

Do you have experience in System design for system development?, Python and TypeScript, Postgres, AWS. Comfort with these is a plus, but strong engineers who have worked in adjacent stacks will pick them up fast., We care more about what you can build than about checking boxes. That said, the following typically maps to success in this role. Core

• 5+ years shipping production software
• Strong backend fundamentals in Python, with willingness to work full-stack in TypeScript when needed
• Solid database design, ideally with Postgres at scale
• Comfort with AWS and modern deployment workflows
• Ability to reason about system design under real constraints: correctness, auditability, and performance on messy real-world data
• Comfort talking to non-technical users and turning what you hear into good software

Nice to have

• Life sciences, clinical trials, or healthcare software experience (EDC systems, clinical data management, regulatory software)
• Production experience with LLM-powered applications (evals, prompt design, structured outputs, tool use)
• Previous startup or founding engineer experience
• Frontend fluency in React
• SOC-2 or HIPAA compliance experience

Pulled from the full job description

• Health insurance
• Paid time off
• Vision insurance
• Dental insurance, * Real problem, real customers, real revenue. We have signed contracts with multiple pharma customers and are running live studies today. You will ship software that touches patient safety data in real trials, not a demo.
• Meaningful equity. Founding-level ownership in a company with commercial traction and strong fundamentals.
• Leadership trajectory. Clear path into Head of Engineering as we scale, with the chance to build and lead the team you want to work on.
• Technical surface area. The domain rewards deep thinking, and the problems range from LLM architecture to distributed systems to compliance engineering.

Location and Work Setup NYC headquarters, hybrid. We are flexible on which days you're in the office, but we expect founding team members to be in person with the team regularly.

Pay: $150,000.00 - $200,000.00 per year

Benefits:

• Dental insurance
• Health insurance
• Paid time off
• Vision insurance

About Octozi Bringing a new drug to market takes over a decade and costs more than a billion dollars. A huge portion of that time and cost sits in clinical trials, where teams of medical reviewers manually comb through patient data looking for errors, inconsistencies, and safety signals before anything reaches regulators. The work is slow, expensive, and error-prone, and it has barely changed in decades. Octozi is changing that. We are building the AI-powered review platform that pharma sponsors and CROs use to clean and review clinical trial data faster and more reliably than manual review. We have signed contracts with multiple pharma customers running live late stage studies, and we are backed by a seed round. Our recent paper documents what the platform achieves on real oncology trial data: 6x faster throughput, 6.4x fewer missed errors, 15.4x fewer false queries, and an estimated $5.1M in savings per Phase III trial. The numbers come from a hybrid architecture combining LLMs, clinical heuristics, and structured human review.