Lead AI Engineer

We are seeking a Lead AI Engineer to define and drive the application of agentic AI across our cloud infrastructure and automation platform. This role sits within the Global Technology organization responsible for the cloud environments that power our business-unit applications, the CI/CD and DevOps toolchain (GitHub, Jenkins, Artifactory, SonarQube, and related tooling), and cloud operations (ITSM).

Responsibilities

• AI-Driven Infrastructure Delivery
  • Design and build AI agents and tools that generate, validate, and refactor infrastructure-as-code – Terraform in particular – to accelerate the delivery of business-unit solutions.
  • Embed guardrails, policy-as-code, and automated validation into the generation workflow so generated infrastructure adheres to standards, security policy, and reusable module patterns before it reaches production.
  • Reduce provisioning lead time and rework by integrating AI-assisted code generation and review into the CI/CD toolchain (GitHub, Jenkins, Artifactory, SonarQube).
  • Curate and maintain a library of reusable Terraform modules, blueprints, and golden patterns that agents can compose to stand up new environments quickly and consistently.
• Agentic AI & LLM Applications
  • Architect and build agentic applications and multi-agent systems using modern agent frameworks (e.g., LangChain, Amazon Bedrock Agents) to automate infrastructure, platform, and operations workflows.
  • Apply and advance emerging agentic techniques such as context engineering, agent harnesses, tool/function calling, and evaluation loops to improve agent reliability and autonomy.
  • Implement RAG pipelines (retrieval-augmented generation) over internal knowledge sources – runbooks, architecture docs, Terraform modules, and ITSM history – to ground agent behavior.
  • Establish patterns and standards for prompt/context engineering, model selection, evaluation, cost management, and responsible-AI guardrails (security, privacy, and hallucination controls).
• AIOps & Cloud Operations
  • Apply AIOps for anomaly detection, event correlation, and automated remediation across the cloud estate and automation platform.
  • Reduce mean-time-to-detect and mean-time-to-resolve by integrating AI into ITSM (ticket triage, classification, routing, and self-healing runbooks) to accelerate cloud operations.
• Platform, Delivery & Leadership
  • Own the LLMOps/agent-ops foundation for agentic AI workloads – pipelines, deployment, evaluation, monitoring, and lifecycle management – on AWS.
  • Partner with security, data governance, and legal teams to ensure AI solutions meet compliance and responsible-AI requirements.
  • Set technical direction, define the AI roadmap for the platform, and provide architecture governance.
  • Mentor engineers, run design reviews, and grow agentic-AI capability across the team.

Qualifications

• Proven experience designing and building AI agents or agentic systems that automate infrastructure, DevOps, or cloud operations workflows.
• Hands-on expertise with infrastructure-as-code (Terraform strongly preferred) and CI/CD toolchains (GitHub, Jenkins, Artifactory, SonarQube).
• Experience architecting and implementing agentic applications using modern frameworks (e.g., LangChain, Amazon Bedrock Agents).
• Familiarity with RAG pipelines, context engineering, and responsible-AI guardrails (security, privacy, hallucination controls).
• Strong background in AIOps, anomaly detection, event correlation, and automated remediation in cloud environments.
• Proficiency in AWS and LLMOps/agent-ops practices, including deployment, evaluation, monitoring, and lifecycle management.
• Ability to set technical direction, define AI roadmaps, and mentor engineers while remaining hands-on with design and implementation.
• Collaborative approach to partnering with security, data governance, and legal teams to ensure compliance and responsible-AI practices.