AI Native Software Engineer - Americas Market

Responsibilities: Design and build production systems spanning frontend, APIs, backend, data, infrastructure, and AI components with integrated architectural decisions Diagnose and resolve production issues across code, networks, infrastructure, identity, data, and AI workloads Engineer cloud-native platforms using containers, Kubernetes, serverless, and infrastructure as code (Terraform, Helm or equivalent) Own the DevSecOps and production engineering lifecycle from commit to production, including CI/CD, testing, security, and release controls Design data flows (transactional, streaming, analytical, unstructured) and data/context architectures for AI systems Develop AI capabilities and agentic systems with evaluation frameworks, observability, and safeguards for trustworthy production use Apply AI-native development practices across the lifecycle (code generation, testing, debugging, modernization, documentation, operations) Lead multidisciplinary engineering teams, set standards, and mentor engineers while engaging with client technologists Turn delivery learnings into reusable patterns, tooling, and standards to influence internal assets and client roadmaps Travel as required (25%–75%)

Key requirements: Minimum 5 years of professional software engineering experience building and operating production systems Minimum 5 years across stack layers: frontend/API through services, data persistence, and async processing Minimum 5 years of programming in Java, Python, Go, TypeScript/JavaScript, or C# Minimum 5 years in cloud platforms (AWS, Azure, or GCP) with containers, orchestration (Docker, Kubernetes) and IaC (Terraform, Helm) Minimum 5 years designing and operating CI/CD pipelines with automated testing and security controls Minimum 1 year designing, building, and deploying AI-enabled or agentic systems in production or near-production Minimum 1 year applying AI-native engineering tools to day-to-day software development Minimum 5 years leading engineering teams or technical workstreams with client-facing delivery client-facing communication cross-functional collaboration ambition and problem ownership Java Python Go