Senior Software Engineer

We're building a world of health around every individual , shaping a more connected, convenient and compassionate health experience.

The Senior Software Engineer will design, build, and ship production-grade AI-powered products and the software and data foundations behind them. You will work with engineering, analysts, data scientists, and product teams in a fast-paced, agile environment, using AI/ML and GenAI to reimagine how healthcare is delivered.

Key Responsibilities

• Design, build, and deploy agentic AI systems and LLM-powered applications, including multi-step workflows, tool use, and orchestration with frameworks such as LangChain and LangGraph
• Develop retrieval-augmented generation (RAG) solutions end-to-end, including ingestion, chunking, embedding generation, vector indexing, retrieval tuning, and grounding of model responses
• Design, build, and maintain the data pipelines, data models, feature stores, and vector stores that feed analytics, ML, and GenAI workloads
• Build full-stack applications that expose AI capabilities to users, including responsive front-end interfaces (e.g., chat and copilot experiences), backend services, and RESTful/GraphQL APIs
• Integrate applications with LLM APIs, relational databases, data platforms, and vector databases, and optimize data access patterns, latency, and token/inference cost
• Implement MLOps/LLMOps practices, including model and prompt versioning, evaluation pipelines, monitoring for quality, drift, and hallucination, and automated release workflows
• Implement CI/CD pipelines, automated testing (including AI evaluation and regression testing), infrastructure as code, and observability across applications, data pipelines, and AI services
• Troubleshoot and resolve production issues across the stack, from data quality and model behavior to API performance and UI experience
• Apply AI-assisted development tools to improve engineering productivity, code quality, and delivery speed, and help establish team standards for their use
• Participate in design and code reviews, mentor junior engineers, and champion engineering and AI best practices
• Partner with product owners, designers, analysts, and data scientists to translate business needs into AI-enabled technical solutions
• Ensure solutions meet security, privacy, and compliance standards (e.g., HIPAA), and apply responsible AI practices including guardrails, PHI/PII protection, auditability, and human-in-the-loop controls

Required Qualifications

• 6+ years of professional software engineering experience, with strong experience building full-stack applications and a track record of delivering AI/ML-enabled solutions to production
• Proficiency in at least one modern backend language (e.g., Python, Java, Node.js/TypeScript) and one modern front-end framework (e.g., React, Angular, Vue)
• Hands-on experience building and deploying Agentic AI solutions in complex cloud infrastructure environments, including orchestration frameworks (e.g., LangChain, LangGraph) and integration with LLM APIs
• Experience building data pipelines to support ML/AI workloads, including feature engineering, embedding generation, and integration with vector databases (e.g., Pinecone, Weaviate, pgvector) for RAG use cases
• Experience designing and building RESTful APIs and microservices, including authentication/authorization, API security, and service-to-service integration, with experience serving AI/LLM capabilities through APIs
• 6+ years of experience working with SQL and relational database management systems, including schema design and query optimization
• 3+ years of experience with cloud platforms and data engineering platforms such as AWS, GCP, Azure, Databricks, or Snowflake
• Familiarity with MLOps/LLMOps practices, model versioning, monitoring, and pipeline support for production ML/AI systems (e.g., Vertex AI, SageMaker, Azure ML)
• Experience with CI/CD, containerization (Docker, Kubernetes), Git-based workflows, and automated testing practices
• Hands-on experience troubleshooting data, application, and AI system issues
• Hands-on experience with performance improvement techniques across data, backend, front-end, and AI inference layers
• Willingness to identify and implement process improvements and best practices, and the ability to take ownership in a fast-paced, collaborative, team-based environment
• Excellent oral and written communication skills, including the ability to translate complex technical and AI concepts for non-technical stakeholders

Benefits

• Medical, dental, and vision coverage
• Paid time off
• Retirement savings options
• Wellness programs
• Other resources, based on eligibility