Shift Technology - Lead AI Engineer
Requirements
• Agentic AI expertise: proven experience building production agentic systems (Microsoft Agent Framework, OpenAI Agents SDK, PydanticAI, LangGraph or custom), and strong command of tool calling, MCP, RAG and evaluation. • Agentic AI expertise: • MLOps and engineering: high proficiency in Python; hands-on experience with experiment tracking, model registry, serving and monitoring (ideally Databricks and MLflow); backend services on Azure, Kubernetes, Terraform and event-driven patterns. • MLOps and engineering: • Applied ML curiosity: solid ML foundations, ability to judge new approaches critically; exposure to graph ML, fraud or claims data is a plus. • Applied ML curiosity: • Software design: high proficiency in Python and strong experience with OOP; proven ability to design robust, maintainable software systems and write clean code, applying the right design patterns and software engineering best practices. • Software design: • Leadership: experience leading technical initiatives across stakeholders, and coaching or managing technical contributors (or a clear motivation to do so). • Leadership: • English fluency required; French is a plus. • English • HOW YOU WORK (Shift High-Impact Behaviors) • 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. • Jump in and get things done: • 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. • Make things simpler: • Test & learn new things: You are genuinely obsessed with the fast-moving AI landscape. You constantly experiment with new models, libraries, and papers, and know how to extract real product value from the hype. • Test & learn new things: • Communicate with impact & help others grow: You lead by example and collaboration, upskilling team members through pair programming, code reviews, and pragmatic design discussions. • Communicate with impact & help others grow: • RECRUITMENT PROCESS • RECRUITMENT PROCESS • A first fit call with our Talent Acquisition Specialist • A couple of interviews to test your leadership & technical skills • A final round at our office with multiple interviews inc. with some of our co-founders • #LI-RH1 #LI-HYBRID • To support our permanent, full time employees at every stage of their careers and lives, we provide a competitive total rewards and benefits package. Here are the global benefits we’d like to highlight: • Flexible remote and hybrid working options • Competitive Salary and a variable component tied to personal and company performance • Multiple Learning and Development opportunities, including Focus Fridays, a half-day each month to focus on learning and personal growth • Generous PTO and paid holidays • Mental health benefits • 2 MAD Days per year (Make A Difference Days for paid volunteering) • Additional benefits may be offered by country, based on your eligibility - ask your recruiter for more information. Intern and Apprentice positions may receive some of these benefits - ask your recruiter for more details. • AI tools are used to help review applications for this role. Read our AI in Recruitment Notice for what the AI considers, how to request a human review, and our most recent bias audit. • AI in Recruitment Notice
Responsibilities
• Build agentic systems (hands-on): design and ship production-grade agentic workflows (LLM orchestration, tool calling, MCP, RAG, structured outputs), and define reference architectures that decide what a model handles and what deterministic code handles. • Build agentic systems (hands-on): • Own LLMOps standards: evaluation harnesses, prompt and agent versioning, tracing (OpenTelemetry), cost and token governance, and release gates, with tenant-aware patterns that respect client data isolation. • Own LLMOps standards: • Evolve our ML platform: be the technical owner of our Databricks-based ML platform (Unity Catalog, MLflow, CI/CD to serving on AKS, monitoring), and extend it toward the agent and prompt lifecycle. • Evolve our ML platform: • Run & Serve Open-Weight Models: Partner closely with our Cloud Ops team to design and deploy the architecture required to self-host open-weight foundation models internally. You will own the inference layer and model optimizations (latency, throughput), while collaborating seamlessly with Cloud Ops on GPU resource provisioning and cluster management. • Run & Serve Open-Weight Models: • Push the frontier: run time-boxed POCs on emerging techniques, such as relational foundation models for claims fraud detection or agentic ingestion of medical billing sources to generate claim edits, with clear success criteria and a path to production. • Push the frontier: • Lead and grow the team: coach and develop 2 to 5 people, raise the technical bar through design and code reviews, and partner with product, SMEs, architecture, security and SRE. • Lead and grow the team:
Benefits
• 2 MAD Days per year (Make A Difference Days for paid volunteering) • Additional benefits may be offered by country, based on your eligibility - ask your recruiter for more information. Intern and Apprentice positions may receive some of these benefits - ask your recruiter for more details. • AI tools are used to help review applications for this role. Read our AI in Recruitment Notice for what the AI considers, how to request a human review, and our most recent bias audit.
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