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.