AI EngineerStraight from Arbital Health’s careers page. Apply on the company site — no recruiter, no middleman.
AI Engineer
Team: Engineering
Location: San Francisco OR Remote
Commitment: Full-Time
Workplace Type: remote
Arbital AI allows users to interact with complex VBC contracts & performance data in natural language and visualize it on demand. The 1st AI-powered platform built for VBC by industry leading healthcare actuaries, Arbital AI makes complex contract performance data conversational, transparent, and instantly actionable.
We are looking for an AI Engineer to help build our next-generation conversational AI experiences. This role sits at the intersection of AI models and the data systems behind them: youll build retrieval and evaluation pipelines and the knowledge systems that ground our models responses in production, working alongside senior engineers while keeping the customer experience front and center.
Is this role right for you?
If you want to make an impact on the US healthcare system, the idea of Arbital AI excites you, and the following matches your skills, experience, and interests:
● Development and deployment of a data-intensive AI product on a SaaS platform
● Programming in Python and SQL
● Learning new frameworks, technologies, tools, and techniques in AI development
● Hands-on experience with prompt engineering, model testing, and automated evaluation techniques for
conversational AI.
● You strive for technically sound solutions that enhance user workflows, demonstrating a talent for iterative improvement and rigorous testing
Impact:
As an AI Engineer at Arbital Health, youll play a pivotal role in shaping the future of value-based healthcare through intelligent automation. Youll help unlock insights from complex financial, clinical, and actuarial data by:
● Help advancing our AI architecture for interacting with complex and unstructured healthcare contract & 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
Responsibilities:
● Collaborate with our cross-functional team of actuarial scientists, data scientists, data engineers, and product managers on Arbital’s AI strategy
● 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
Requirements:
● More than one year in machine learning or AI-related roles
● Familiarity with cutting-edge AI systems, context engineering and agentic systems ranging from tool-calling stacks to MCP-style frameworks
● Familiarity with AI orchestration frameworks like LangChain, ADK, etc.
● Familiarity with maintaining context engineering pipelines (RAG, memory, summarization, compression, grounding) for conversations.
● Proficiency in Python and Cloud ML Services like Vertex AI, AWS Bedrock and SageMaker
● Experience with Airflow, Databricks, and AWS or GCP
● Ability to ship extremely high-caliber code and build exceptional products
● 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.
Tools we use:
● AI: Vertex AI, GCP Model Garden, MLflow, Databricks Vector Search
● Core Tools: Python, R, SQL, Next.js, React, TypeScript, Tailwind CSS
● IDE: Cursor, Claude Code, and R Studio
● Version Control: GitHub
● Team Planning / Design: Jira, Confluence, Claude, Gemini
• Applicants must be legally authorized to work in the United States for the duration of their employment.
• This position is not eligible for employer-sponsored immigration sponsorship, now or in the future. • Applicants must be able to work in the United States without requiring employer sponsorship.
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