Senior / Staff AI Software Engineer

About Aegis Ventures

Aegis Ventures partners with entrepreneurs and industry leaders to launch and scale transformative companies in digital health and artificial intelligence. Our platform brings together market-shaping ideas, growth capital, and ambitious individuals to solve major societal problems. With a focus on innovations in healthcare, Aegis has launched four successful portfolio companies in partnership with Northwell Health and recently announced the Digital Consortium to co-develop, invest in, and launch new companies.

About Caregentic

Caregentic is transforming how healthcare organizations deliver patient care in the real world by developing a modern platform with AI-powered patient engagement. We’re solving complex challenges in patient care with sophisticated technology: Care journey orchestration, health data integration, and clinical workflows. We relieve healthcare providers of daily frustrations, so they can focus on what matters most: caring for patients.

Founded by a team that understands both the technical challenges and clinical realities of modern healthcare, we're co-developing a platform with leading health systems like Northwell Health, giving us access to real-world feedback and validation from day one. This unique partnership means our work is refined and improved in real clinical environments.

We're at an exciting inflection point — our early customers are seeing measurable improvements in care delivery and operational efficiency, and we’re ready to grow our team with an experienced, senior engineer who can help scale our impact in the industry.

About the Job

As a Senior or Staff AI Software Engineer at Caregentic, you will have end-to-end ownership of key parts of our backend services architecture and our AI-drive applications. You will work on our modern micro-service architecture, built with Python 3.12, FastAPI, Strawberry GraphQL, and event-driven design principles.

You will be responsible for building scalable, resilient systems that drive real impact in patient care while also helping shape the technical direction of the platform and mentoring other engineers. Our team operates with the urgency that healthcare demands, and we never lose sight that our work directly impacts patient lives.

We’ve been a fully remote team from the start, distributed across the U.S. We believe that great engineering happens wherever people do their best work.

Our Tech Stack:

• Python 3.12, FastAPI, Strawberry GraphQL
• PostgreSQL with asyncpg and SQLAlchemy
• Procrastinate (background jobs) and Apache Kafka
• Docker, Kubernetes, AWS (S3, Cognito, SES, etc.)
• Apollo Federation (GraphQL gateway)
• React and TypeScript web frontend
• Rasa (fork) with spaCy 3, Rasa SDK (custom action server)
• LangChain, LangChain, AWS Bedrock, LangSmith (tracing/evals)
• Vector search: Databricks Vector Search

What You'll Do:

• Design and develop robust, scalable, event-driven services using Python, FastAPI, Apache Kafka and GraphQL.
• Build fundamental LLM agents and integrate them into our product.
• Work with DevOps on deployments, monitoring, and reliability improvements.
• Maintain and optimize PostgreSQL databases and data models.
• Collaborate across product and engineering teams to define requirements and architect features.
• Drive engineering best practices through code reviews and mentorship.
• Engage with current and prospective clients to drive understanding of the Caregentic AI architecture and capabilities.
• Design, build, and operate LLM services, including RAG systems (LangChain), agentic workflows, and evaluation pipelines (LangSmith, deepeval, A/B testing).
• Own vector search & embeddings pipelines from schema and metadata design to model benchmarking, cost/latency optimization, and Databricks Vector Search integration.
• Lead conversational AI development enhancing NLU policies, safety guardrails, and custom action servers, plus integrating assistants with microservices.

What You'll Need:

• 7+ years of backend development experience in production environments, specifically strong Python skills, including async programming and type hints.
• Experience building and monitoring production-quality ML and AI systems.
• Hands-on expertise with RAG frameworks and agentic workflows. 
• Solid understanding of PostgreSQL database design and optimization.
• Familiarity with Docker and containerization.
• Strong testing practices using pytest.
• Experience with micros