Senior AI Engineer, Conversational AI & Agentic Systems

Location: NY, NY (Remote within the US)
Reports To: Director of AI Engineering
Compensation: $200,000–$300,000 base + equity

Blooming Health is a mission-driven, venture-backed health tech company transforming the social care landscape. We’re building an intelligent platform that helps people navigate and access the resources essential for holistic well-being—enabling CBOs, health systems, and health plans to deliver more effective and equitable care.

We’re hiring an AI Engineer to help us design and build the systems that power our AI experiences—especially LLM-driven workflows, conversational patterns, and orchestration/agent layers. You’ll work closely with the Director of AI Engineering and product/engineering partners to ship reliable AI features into production, with strong attention to evaluation, data, and software quality.

• Brainstorm and design AI orchestration patterns: how agents hand off, how state flows, how to handle uncertainty and edge cases.

• Build and maintain our AI orchestration layer (Master OS, Engines, agent workflows).

• Think through tradeoffs in prompt design, tool architecture, and conversation flow.

• Design data pipelines that capture, transform, and surface insights from patient/member interactions.

• Write clean, tested, production-ready Python (APIs, services, orchestration code).

• Be a thought partner on technical direction—we’re building something new and need someone who enjoys solving hard problems together.

AI / LLM Foundations

• Hands-on experience with LLM APIs (OpenAI, Anthropic, or similar).

• Understanding of prompt engineering patterns and limitations.

• Familiarity with conversational AI / chatbot architectures.

• Ability to reason about AI system design: when to use agents, how to structure workflows, how to handle uncertainty.

Python Proficiency

• Comfortable with async Python (asyncio, httpx, aioredis).

• Experience building APIs and backend services.

• Strong grasp of clean code principles and testing.

Data Engineering Fundamentals

• Strong SQL (PostgreSQL preferred).

• Experience building ETL pipelines / data workflows.

• Understanding of data modeling and schema design.

AI / LLM Depth

• Orchestration patterns: multi-agent systems, tool use, function calling.

• RAG, embeddings, retrieval systems.

• Voice AI / real-time audio (Twilio, WebRTC, speech-to-text).

• Familiarity with evaluation/testing strategies for AI systems.

Data Engineering Depth

• Streaming data (Kafka, event-driven architectures).

• Orchestration tools (Airflow, Prefect, Dagster).

• dbt or similar transformation frameworks.

Healthcare Domain

• Healthcare workflows, HIPAA considerations.

• SDOH, care management, patient engagement experience.

Infrastructure

• Docker, Kubernetes, container orchestration.

• Cloud platforms (GCP, AWS).

• Impact: Help improve access to social care and advance health equity.

• Innovation: Build real AI systems that ship—agents, orchestration, data, and evaluation.

• Growth: Take real ownership and grow fast with the product and team.

• Team: Mission-driven people who move quickly and care about doing it right.