[Hiring] AI Developer @Massive Bio

Role Description

We're looking for an AI Developer to join our engineering team and build intelligent healthcare agents on our Agent Studio platform. You'll design, develop, and deploy AI-powered microservices that process medical records, match patients to clinical trials, and integrate with healthcare data standards, all within a modern, event-driven architecture. This is a hands-on engineering role where you'll write production code daily, work with LLMs, vector databases, and healthcare data formats, and ship features that directly impact patient outcomes.

What You'll Do

• Build AI agents as Python microservices using our SDK (massivebio-agent-sdk)
• Design and implement multi-agent pipelines for medical data processing (OCR, clinical abstraction, terminology mapping, FHIR generation)
• Integrate LLMs (GPT-4o, GPT-5) for clinical text extraction, summarization, and decision support
• Work with vector databases (Qdrant) for semantic search, RAG, and terminology resolution
• Build and maintain integrations with healthcare systems (Azure FHIR, HL7, SNOMED CT, RxNorm, LOINC)
• Develop dashboard features for agent management, monitoring, and deployment
• Write clean, tested, production-ready code with proper error handling and observability
• Collaborate with clinical teams to translate medical workflows into agent pipelines

Qualifications

• 3+ years of professional software development experience
• Professional proficiency in English, both written and spoken
• Strong Python skills (async/await, Pydantic, FastAPI or similar frameworks)
• Experience with LLMs prompt engineering, function calling, RAG pipelines, or fine-tuning
• REST API design and implementation
• SQL proficiency (PostgreSQL preferred)
• Git workflow (branching, PRs, code review)
• Comfortable with Docker and containerized deployments
• Strong problem-solving skills and ability to work independently

Requirements

• Experience with healthcare data (FHIR, HL7, ICD-10, SNOMED CT, medical records)
• Azure cloud services (Container Apps, Service Bus, Cosmos DB, Key Vault, Blob Storage)
• Vector databases (Qdrant, Pinecone, Weaviate) and embedding models
• OpenTelemetry or distributed tracing experience
• TypeScript/React (Next.js) for dashboard frontend contributions
• Experience building event-driven architectures (message queues, pub/sub)
• CI/CD pipelines (Azure DevOps, GitHub Actions)
• Knowledge of clinical trials, oncology workflows, or biotech domain
• Experience with CRM integrations (HubSpot, Salesforce)

Tech Stack

• Language: Python 3.12, TypeScript
• Backend: FastAPI, Pydantic v2, asyncio
• Frontend: Next.js 15, React 19, Tailwind CSS
• AI/ML: GPT-4o/5, Azure OpenAI, LLM Gateway, RAG
• Databases: PostgreSQL, Cosmos DB (MongoDB API), Qdrant
• Messaging: Azure Service Bus (queues, topics)
• Healthcare: Azure FHIR (R4), SNOMED CT, RxNorm, LOINC
• Infrastructure: Azure Container Apps, Docker, Azure DevOps CI/CD
• Observability: OpenTelemetry, Azure Monitor
• Package Management: uv, Azure Artifacts (private PyPI)

How You'll Work

• Agents as microservices — each agent is a standalone Python service that extends BaseAgent and implements a single process() method
• Built-in platform services — agents access LLM Gateway, Vector DB, PostgreSQL, HubSpot CRM, and FHIR Server via SDK clients (self.llm, self.vectordb, self.postgres, etc.)
• Event-driven pipelines — agents communicate via Azure Service Bus queues and topics
• One-click deployment — push code to GitHub, deploy from the Agent Studio dashboard
• Full observability — execution tracking, token usage monitoring, distributed tracing across agent pipelines