Engineering Manager, AI Platform

Overview

In this role, you lead the AI Platform’s Applied AI and Data Science team to deliver production-grade, AI-powered capabilities for internal and external users. You balance hands-on coding with people leadership, shaping the architecture for agentic AI, NLP, and ML systems. You collaborate with product, data engineering and business stakeholders to decide what to build and ensure measurable impact. You champion AI-native engineering and drive trusted, compliant AI solutions at scale.

Pay / Benefits

• Pension or 401(k) plan
• Private health insurance
• Employee assistance program (24/7 wellbeing resources)
• Work From Anywhere up to 25 days/year
• Generous annual and parental leave
• Volunteer and relocation days with moving home support? (explicit phrase)

Responsibilities

• Lead and grow the multidisciplinary AI/ML team across engineering and data science
• Own delivery planning, resourcing, prioritisation and alignment with product management
• Communicate progress, risks and trade-offs to leadership and stakeholders
• Remain hands-on by contributing to code, models and architecture decisions
• Shape architectural direction for agentic AI, RAG, NLP and ML systems
• Oversee safe and reliable agents with guardrails and human-in-the-loop controls
• Maintain quality, security, compliance, testing and observability standards
• Promote AI-native engineering practices across the SDLC with coding agents
• Collaborate with Product, Data Engineering, Security, Legal and business units
• Hire, onboard and develop team skills to match the AI roadmap
• Drive CI/CD, experiment tracking and production readiness across the team

Key requirements

• Engineering manager or tech lead with direct people-management of AI/ML engineers, NLP engineers and/or data scientists
• Strong hands-on AI/ML engineering background with Python proficiency
• Experience with modern agent frameworks (e.g., Strands Agents, LangGraph, Claude Agent SDK) and interoperability standards (MCP, A2A)
• Cloud-native AWS expertise (Bedrock, Bedrock AgentCore, SageMaker, Lambda, Step Functions) and IaC (CDK)
• Hands-on LLMOps/MLOps experience including evaluation, guardrails, cost monitoring and automated pipelines
• Understanding of AI security risks (prompt injection, data leakage, over-permissioned tools) and mitigations
• Experience delivering AI-native software with coding agents across planning, coding, testing and review
• Ability to set standards for AI-assisted development and evaluate AI-generated code
• Solid grounding in applied data science to lead data scientists and challenge work
• Excellent communication to explain trade-offs to non-technical stakeholders
• Strong product sense to scrutinize and refine requirements
• Excellent communication
• Collaborative and cross-functional mindset
• Strategic and product-minded thinking
• Python
• LLM/ML engineering
• Agent frameworks (Strands Agents, LangGraph, Claude Agent SDK)

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