AI/ML Engineer

Role Description

As an AI/ML Engineer, you’ll work across backend systems, data pipelines, and AI/ML systems. You’ll help architect and build multi-agent systems, work across LLM development, agent orchestration, evaluation and deployment, owning the full development from prototype to production.

As an early member of the engineering team, you’ll have real ownership and influence: shaping architecture, defining standards, and building systems that carriers, brokers, and employers rely on every day.

What You’ll Do

• Develop AI-native workflows
• Architect and build scalable multi-agent systems with clear evaluation metrics, monitoring, fallback strategies, and cost controls for extracting and reasoning over complex benefits data.
• Own backend and data-heavy systems
• Design and own backend services, APIs, and data pipelines that power AI workflows, with a focus on correctness, scalability, observability, and long-term maintainability.
• Collaborate cross-functionally
• Work closely with Product, Design, Sales, and Client teams to understand customer workflows and translate them into durable technical solutions.
• Continuously improve systems
• Refine existing architecture, reduce operational complexity, and help define what “great” looks like as the platform scales.

Qualifications

• A full stack engineer with 3+ years of experience building complex web applications
• Comfortable owning backend systems and APIs, while collaborating closely on frontend experiences
• Experienced integrating AI / LLM-powered systems into real products
• Curious, adaptable, and energized by working in fast-moving, ambiguous environments
• A collaborative partner to product managers, designers, and other engineers

Requirements

• 3+ years of experience in software engineering
• Strong backend engineering experience with Node.js and Python
• Hands-on experience integrating and operating AI systems using frameworks such as LangGraph, LangChain, LlamaIndex, and model SDKs (OpenAI, Anthropic, Google AI Studio), including prompt/version management and tool calling
• Bonus: AWS, MySQL at scale, and JavaScript frameworks
• Experienced building, deploying, and operating multi-step or multi-agent AI systems in production, with ownership of correctness, latency, cost, and failure handling
• Experienced designing and operating RAG or persistent memory systems using vector databases (e.g., Pinecone, Turbopuffer), including indexing strategies, retrieval evaluation, and performance/cost tradeoffs
• Experienced building production-grade evaluation and monitoring pipelines for AI systems (e.g., LangSmith, Langfuse, MLflow), including offline evals, live metrics, and regression detection
• Experience building document ingestion pipelines, structured extraction, chunking strategies, and handling noisy or inconsistent source documents
• Experience in insurance, healthcare, or financial services is a plus, but not required.

Benefits

• Meaningful ownership: Build foundational systems used by carriers, brokers, employers, and employees at scale
• Real impact: Your work directly improves how people understand and use their benefits
• Growth: Join early and grow with the company as we scale our product, team, and distribution
• Competitive compensation: Salary, meaningful equity, and full benefits: medical, dental, vision, 401(k) with match, life insurance, and flexible PTO
• Remote‑first: Work from anywhere in the U.S. with a highly collaborative team

The interview process

• Silver screening Interview
• Silver Technical Interview
• Client Screening Interview
• Client Technical interview
• Client Behavioral Interview