As a Senior AI Software Engineer, you will own the design and development of end-to-end AI systems, spanning backend infrastructure, model orchestration, and production-grade deployment. You'll work closely with product, data, and infrastructure teams to integrate LLMs, agentic frameworks (LangGraph, LangChain, AutoGen), computer vision models, and vector-based reasoning systems into consumer-facing and internal tools. This role is highly technical, hands-on, and requires both deep systems expertise and practical AI application skills. If you're a high-ownership engineer excited to ship AI-powered products at scale, this is your opportunity to make a real impact.
Key Responsibilities
- Design, build, and scale distributed backend systems that power LLMs, agents, and AI infrastructure.
- Integrate AI/LLM models into product systems (e.g., LangGraph, Agentic APIs, vector stores, orchestration layers).
- Develop high-reliability APIs and services for real-time AI inference, telemetry, usage metering, and monitoring.
- Own backend architecture decisions across authentication, billing, deployments, and developer platforms.
- Collaborate closely with product, infra, and research teams to translate cutting-edge AI into production systems.
- Ensure production-readiness through observability, CI/CD pipelines, and SRE-style reliability engineering.
- Drive continuous improvement, pushing for faster iteration, scalability, and throughput.
- Mentor peers and lead by example with a hands-on, high-ownership, startup-style mindset.
Must-Have Qualifications
- 5+ years of experience building production-grade backend systems in Python, Go, or similar.
- Deep experience with distributed systems, microservices, and event-driven architecture.
- Strong grasp of AI/ML infrastructure, model inference, model serving, and agentic frameworks.
- PostgreSQL, Redis, or similar data store expertise, including performance tuning and scaling.
- Familiarity with vector databases, embeddings, and LLM-specific storage/search systems.
- Experience deploying in cloud-native environments (AWS, GCP) using Kubernetes, Terraform, Docker.
- Proficiency with API design, backend frameworks (e.g., FastAPI, Flask), and load balancing.
- Hands-on experience with telemetry, monitoring, logging, and production issue triage.
- Understanding of CI/CD workflows, developer tooling, and test automation at scale.
- Ability to work in fast-paced, early-stage environments, making tradeoffs and shipping quickly.
- Strong communication skills: clear, concise, and collaborative-even when disagreeing.
- Bias for action: you're a scrappy problem solver who thrives in ambiguity.
Nice-to-Have Qualifications
- Experience with LangChain, LangGraph, AutoGen, OpenAI APIs, or other agent-based orchestration frameworks.
- Familiarity with computer vision models and multimodal AI systems.
- Background in health tech, regulated data systems (HIPAA compliance), or medical data pipelines.
- Experience building AI-powered consumer applications with personalization and real-time inference.
- Exposure to reinforcement learning, retrieval-augmented generation (RAG), or long-term memory agents.
- Motivated by a mission-driven product, with excitement for being part of explosive growth.
- Background in competitive sports, military, or other high-intensity, high-throughput environments where resilience and ownership are key.
Why Join Us
- Work on cutting-edge AI products that directly help people improve their health.
- Build agentic systems from the ground up, influencing technical strategy and architecture.
- Join a fast-moving, high-ownership team, with significant autonomy and impact.
- Competitive compensation, equity, and benefits in a rapidly scaling health tech company.
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