Job Description
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. Apply tot his job
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