Staff AI Engineer

Shift delivers AI agents that transform insurers' most critical work. By combining deep industry expertise and unmatched data resources, Shift provides proven results that have earned the trust of hundreds of the world's leading insurers. Our insurance-grade AI is accurate, explainable, and secure—empowering human experts to move with unmatched speed, total confidence, and a renewed focus on the people they serve.

Our culture is built on innovation, trust, and a drive to transform the insurance industry through our SaaS platform. We come from more than 50 different countries and cultures and together we are creating the future of insurance.

At Shift, we are building the next generation of AI-driven platform capabilities. We are looking for an experienced, hands-on Staff AI Engineer to serve as the technical anchor for our AI capabilities; someone who is deeply passionate about building, prototyping, and scaling modern AI/LLM systems, while helping shape our broader AI engineering strategy.

This is a high-impact, high-visibility role for a senior builder who excels at the intersection of cutting-edge AI technologies (Agentic frameworks, LLM orchestration, MCP, GenAI) and production-grade software engineering. You will work directly with data scientists, software engineers, and product leaders to design, prototype, and ship state-of-the‑art AI systems into production.

If you are a senior AI engineer looking for the next step in your career -where you can drive architectural strategy and mentor others without giving up hands‑on coding and building- this role is for you.

WHAT YOU'LL DO

• Build & Architect Agentic Systems (Hands‑On): Lead by doing. Design, prototype, and build production‑ready agentic workflows, custom orchestration layers, and tool‑calling integrations using modern frameworks.
• Bridge AI & Production Engineering: Move AI prototypes into robust, production‑grade microservices on Azure. Ensure AI components are scalable, low‑latency, and well‑integrated into the broader tech stack.
• Implement Next‑Gen AI Standards: Experiment with and integrate emerging paradigms into our production stack, including Model Context Protocol (MCP), advanced RAG patterns, vector pipelines, and structured LLM outputs.
• Drive AI Quality & LLMOps: Establish and implement operational frameworks for experiment tracking, evaluations, prompt engineering, latency optimization, token budget governance, and model observability.
• Influence & Upskill: Act as a technical mentor for agent‑focused engineering squads. Lead technical design reviews, set coding standards, and help elevate the team's AI engineering capabilities.
• Stay at the Cutting Edge: Continuously benchmark new models, AI tools, and architectures, translating relevant breakthroughs into practical, value‑driving implementations at Shift.

WHAT WE ARE LOOKING FOR

We are seeking a seasoned AI engineer who combines deep, practical expertise in modern GenAI/LLM ecosystems with strong backend software engineering skills.

Deep AI & Agentic Expertise:

• Hands‑On Agentic Frameworks: Proven experience building with frameworks like Microsoft Agent Framework, LangGraph, LlamaIndex, OpenAI Agents SDK, or custom orchestration frameworks.
• LLM Patterns & Tooling: Practical experience with Model Context Protocol (MCP), tool/function calling, structured LLM outputs, and complex RAG pipelines (vector retrieval, hybrid search, embeddings).
• LLMOps & Observability: Experience with evaluation frameworks, prompt engineering, tracing, context window optimization, and compute/token governance in production.

Production Engineering & Stack:

• Programming: High proficiency in Python (required for AI ecosystem work) paired with strong experience in OOP.
• Cloud & APIs: Experience building and scaling backend microservices and REST/OpenAPI endpoints in enterprise cloud environments (specifically Azure).
• Data & Events: Familiarity with vector databases, relational databases, and event‑driven patterns (e.g., Azure Service Bus, Kafka).
• Engineering Rigor: Comfortable with containerization (Docker, Kubernetes), CI/CD, testing methodologies, and Infrastructure as Code (Terraform or Bicep).

HOW YOU WORK

• Jump in and get things done: You are a proactive builder who loves turning ambitious ideas into working code. You don't wait for permission to solve hard problems.
• Make things simpler: You can break down complex AI concepts and architectures into clear, executable steps for engineers, data scientists, and non‑technical partners alike.
• Test & learn new things: Y