Senior Back End Engineer (API & Agentic AI)

QuantHealth is an AI startup revolutionizing drug development and clinical trials. Our cutting-edge clinical trial simulator can run thousands of trials in parallel to de-risk and optimize real-world clinical trials. Powered by a unique dataset of over 350M patients and 100K drugs, our platform helps drastically reduce drug development costs and timelines. We’re venture-backed, based in Israel, and work with top-tier pharma companies across Europe and the US. 

We are looking for a Senior Back End Engineer (API & Agentic AI) to play a key role in the evolution of QuantHealth’s backend architecture and emerging AI platform capabilities. This role will contribute significantly to the transition from a monolithic application to a multi-service backend platform, while also helping design and implement the backend foundations for agentic AI systems used across our product.

You will work on core backend services, API design, and distributed system concerns, and collaborate closely with full stack, product, data science, and security teams to build scalable, secure, and well-observed services that support both human-facing workflows and autonomous AI agents.

Backend & Platform Architecture

• Contribute to the design and implementation of a multi-service backend architecture

• Design, build, and maintain robust, well-documented APIs for internal and external consumers

• Help define backend standards that support both traditional SaaS workflows and AI-driven, agent-based execution

• Collaborate on architectural decisions and provide technical guidance within the engineering team

Agentic AI Enablement

• Design backend primitives and services that support agentic AI systems (e.g., task execution, state management, orchestration, tool invocation)

• Build APIs and infrastructure that allow AI agents to safely interact with internal services, data, and external systems

• Implement guardrails for agent execution, including authorization boundaries, auditability, rate limits, and failure handling

• Partner with data science and ML engineers to productionize AI workflows in a reliable, observable, and secure way

Backend Best Practices & Reliability

• Implement and improve backend best practices, including:

  • Authentication and authorization (token-based auth, RBAC, service-to-service auth)

  • Idempotency and safe retry mechanisms

  • Consistent error modeling and API contracts

  • Input validation and schema enforcement

  • API versioning and backward compatibility

• Ensure backend services follow strong networking and security principles

• Help establish and maintain observability standards (logging, metrics, tracing)

• Write high-quality, well-tested TypeScript code

• 7+ years of professional software engineering experience, primarily focused on backend systems

• Strong expertise in TypeScript for server-side development

• Proven experience designing and implementing APIs for complex systems

• Experience with Nest.js or another major TypeScript backend framework (e.g., AdonisJS, Express, Fastify, Koa)

• Solid understanding of:

  • HTTP and networking fundamentals

  • API security and authentication/authorization patterns

  • Reliability concerns in distributed systems

• Experience with:

  • API documentation (OpenAPI / Swagger)

  • Testing strategies (unit, integration, API tests)

  • Validation and contract-driven development

• A pragmatic, ownership-oriented mindset with strong engineering judgment

• Comfort working in systems that mix deterministic software with probabilistic AI components

• Experience participating in monolith-to-services or modularization efforts

• Experience supporting external, customer-facing APIs

• Experience designing systems that support AI agents, workflows, or automation platforms

• Familiarity with LLM tooling concepts (tools/functions, agent loops, structured outputs)

• Experience with Effect

• Familiarity with healthcare, life sciences, or regulated environments

• Experience with cloud-native deployments and production observability tooling

• Work on technically deep problems at the intersection of backend systems and AI in healthcare

• Help shape both a scalable backend platform and the foundations of agentic AI capabilities

• Collaborate with a thoughtful, high-caliber engineering team

• Competitive compensation and opportunities for growth