Software Engineer, AI - Dunkirk / Buffalo NY

Company Overview ImmunityBio is a vertically integrated commercial stage biotechnology company developing next-generation therapies that bolster the natural immune system to defeat cancers and infectious diseases. The Company’s range of immunotherapy and cell therapy platforms, alone and together, act to drive and sustain an immune response with the goal of creating durable and safe protection against disease. Designated an FDA Breakthrough Therapy, ANKTIVA is the first FDA-approved immunotherapy for non-muscle invasive bladder cancer CIS that activates NK cells, T cells, and memory T cells for a long-duration response. The Company is applying its science and platforms to treating cancers, including the development of potential cancer vaccines, as well as developing immunotherapies and cell therapies that we believe sharply reduce or eliminate the need for standard high-dose chemotherapy. These platforms and their associated product candidates are designed to be more effective, accessible, and easily administered than current standards of care in oncology and infectious diseases.

Why ImmunityBio?

• ImmunityBio is developing cutting-edge technology with the goal to transform the lives of patients with cancer and develop next-generation therapies and vaccines that complement, harness and amplify the immune system to defeat cancers and infectious diseases.
• Opportunity to join a publicly traded biopharmaceutical company with headquarters in Southern California.
• Work with a collaborative team with the ability to work across different areas of the company.
• Ability to join a growing company with professional development opportunities.

Position Summary The Software Engineer – AI is a hands-on role integrating data engineering, software development, and AI agent architecture, working closely with platform engineering, data science, security, and product teams. The Software Engineer – AI will contribute to AI agent development and collaborate with cross-functional teams on the implementation of production-grade AI systems. This role supports Engineering leadership by implementing change-controlled solutions, helping maintain project schedules and quality standards, and providing technical support for daily AI-powered operations — including the implementation and improvement of agent frameworks and supporting infrastructure.

Essential Functions

• Contribute to the design, development, maintenance, and deployment of AI agent systems, including one or more of LangGraph StateGraph patterns, CrewAI multi-agent orchestration, LlamaIndex data/agent workflows, or related frameworks.
• Design, build, and maintain FastAPI-based agent servers, including async/await endpoints, streaming responses, and health check endpoints, following established architecture and coding standards.
• Implement comprehensive testing strategies — unit, integration, edge-case, and performance — for agents and services to ensure production reliability.
• Implement and extend guardrails for AI interactions, including input/output validation, safety checks, prompt hardening, policy enforcement, and robust error handling in alignment with organizational security and compliance standards.
• Implement secure tool execution patterns adhering to least-privilege access, allowlists, secrets management, audit logging, and validation controls against prompt injection/data exfiltration under guidance from senior engineers.
• Implement agent observability including per-step traces, tool-call telemetry, cost/latency budgets, and SLO-based alerting using existing monitoring and logging platforms.
• Help design and maintain agent evaluation sets, adversarial tests, regression tests, and monitoring for safety/quality drift.
• Design and build RAG/retrieval pipelines using vector databases such as Chroma, Milvus, Weaviate, and Qdrant, working with data and platform teams on schema and performance.
• Collaborate with SMEs across Platform Engineering, Data Science, Security, Quality, and Product to ensure agent systems meet technical and operational requirements.
• Contribute to the creation, modification, and maintenance of AI system documentation, including architecture decision records (ADRs), runbooks, API specifications, network topology diagrams, data flow diagrams, and best-practice guides.
• Provide technical input regarding operability, technical feasibility, engineering design, security posture, maintainability, and documentation …