Design and build intelligent cloud-native applications that combine modern software engineering with emerging AI capabilities
Develop APIs, microservices, and distributed systems that support AI-driven features, autonomous workflows, and real-time inference
Integrate advanced AI frameworks such as Microsoft Agent Framework, LangChain/LangGraph, Semantic Kernel, and Autogen to build reasoning engines, orchestrators, and agent-based experiences
Prototype, evaluate, and productionize AI features, from retrieval-augmented pipelines to multi-agent collaboration patterns
Use AI engineering tooling (GitHub Copilot, Claude Code, etc.) to improve development velocity, code quality, and experimentation
Shape architectural patterns for AI systems, including prompt pipelines, vector storage, model orchestration, and scalable inference services
Ensure all solutions meet the highest standards for security, governance, resiliency, compliance, and responsible AI
Contribute to DevOps maturity, including CI/CD automation, environment consistency, and repeatable deployment patterns
Collaborate with product, AI, cloud, and engineering teams to deliver modern, intelligent, high-impact user experiences
Thrive in an environment where priorities shift quickly as we explore new capabilities and unlock new opportunities with AI

8 + years of engineering experience, ideally building enterprise-grade or regulated systems
Strong foundational skills in Python (preferred), Javascript/Typescript, Rust, Go or other modern programming languages with demonstrated backend or full-stack proficiency
Hands-on experience with Cloud engineering (Azure preferred) including serverless, identity & access, compute, networking, and storage
Equivalent knowledge in AWS or GCP will certainly be considered
Working knowledge of Kubernetes, microservices, and distributed system design
Proficiency with Infrastructure as Code (IaC), Observability as Code (OaC) and Terraform
Experience with AI agent and orchestration frameworks such as (but not limited to) Microsoft Agent Framework, LangChain/LangGraph, Semantic Kernel, Autogen, etc.
Familiarity with LLM integration patterns, retrieval systems, embeddings, vector search, prompts, and evaluation tooling
Comfort using AI-accelerated development tools like GitHub Copilot or Claude Code
Experience implementing CI/CD pipelines with GitHub Actions
Strong problem-solving skills — especially when diagnosing complex, distributed, or AI-dependent behaviors

health, dental, mental health, vision, short
and long-term disability, life and AD&D insurance coverage
adoption/surrogacy and wellness benefits
employee/family assistance plans
various retirement savings plans (including pension and a global share ownership plan with employer matching contributions)
financial education and counseling resources
generous paid time off program including holidays, vacation, personal, and sick days
full range of statutory leaves of absence

Senior AI Full-Stack Engineer

Key skills