Sr. AI Engineer
Team: Engineering
Location: San Francisco OR Remote
Commitment: Full-Time
Workplace Type: hybrid
Salary:
Impact:
- As a senior AI engineer at Arbital Health, you'll play a pivotal role in shaping the future of value-based healthcare through intelligent automation. You'll help unlock insights from complex financial, clinical, and actuarial data by:
- Owning the conversational AI architecture for interacting with complex and unstructured healthcare contract and financial data, delivering real-time analytics and visualizations
- Driving the evaluation and production-scale deployment of LLMs within a HIPAA-compliant environment
- Dramatically reducing analytics time for strategic decision-making
- Supporting thought leadership in the intersection of value-based care, healthcare finance, and artificial intelligence
Responsibilities:
- Lead the architecture and development of Arbital’s next-generation conversational AI
- Collaborate with our cross-functional team of actuarial scientists, data scientists, data engineers, and product managers on Arbital’s AI strategy and help shape the conversational AI platform roadmap
- Manage the deployment and monitoring of these AI solutions in production environments to ensure they are performing as expected and troubleshoot any issues
- Ensure data accuracy, integrity, privacy, security, and compliance through automated quality control procedures
- Mentor junior team members
Requirements:
- 8+ years of experience in data-intensive, SaaS platform development projects
- 2+ years of experience with cutting-edge AI systems, context engineering and agentic systems ranging from tool-calling stacks to MCP-style frameworks
- Hands-on experience with AI orchestration frameworks like LangChain, CrewAI, ADK, etc.
- Demonstrable experience designing and building conversational AI systems that exhibit autonomous behavior, decision-making, and/or tool usage.
- Experience in designing and maintaining context engineering pipelines (RAG, memory, summarization, compression, grounding) for conversations.
- Proficiency in Python and common AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers, LangChain, LlamaIndex).
- Solid understanding of MLOps principles and experience with tools for model deployment, monitoring, and CI/CD for ML.
- Standing up observability for agents (traces, costs, failures, hallucinations, guardrails) and creating dashboards that guide product decisions.
- Experience with Cloud ML Services like AWS Bedrock, SageMaker, and Google Vertex AI
- Experience with Airflow, Databricks, and AWS or GCP
- Ability to ship extremely high-caliber code and build exceptional products
- Ability to perform under minimal supervision with accountability for specific objectives and work in a rapidly changing, ambiguous start-up environment
- Passionate about improving and innovating
- Our team works hybrid from the San Francisco Bay Area. We will prioritize candidates who can work two days per week from our San Francisco office. We will also consider highly qualified remote candidates who can travel to San Francisco for in-person collaboration several days per month.
Nice to have's:
- Startup experience is highly preferred
- Product development coding in R
Tools we use:
- Infrastructure: AWS, GCP, Databricks, Airflow, Sigma, Datadog
- AI: Vertex AI, Vanna AI, Databricks Vector Search
- Core Tools: Python, R, SQL, Next.js, React, TypeScript, Tailwind CSS
- IDE: Cursor, VS Code, and R Studio
- Version Control: GitHub
- Team Planning / Design: JIRA, Confluence, Figma, Lucid
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