Group Engineering Leader, Product Engineering (PxE Platforms)

About This Role

Lead an engineering workstream to deliver cloud-native products and Generative AI capabilities, guiding technical execution and partnering with stakeholders to translate requirements into secure, reliable software.

Responsibilities

• Own delivery for an engineering workstream (scope, plan, dependencies, risks), coordinating engineers, product, QA, and platform/security partners
• Produce and socialize system designs, driving design reviews and technical tradeoffs
• Design and build front-end and back-end components, review code, improve test coverage, and drive pragmatic engineering standards
• Deliver GenAI features using patterns like Retrieval Augmented Generation (RAG), prompt design, tool/function calling, and agent-style workflows
• Build and maintain multi-step GenAI workflows using LangGraph, including traceability and evaluation
• Build and operate solutions on AWS, Azure, and/or Google Cloud Platform using PaaS, FaaS, containers, and microservices
• Implement continuous integration/continuous delivery (CI/CD), quality gates, security scanning, and release practices
• Apply Site Reliability Engineering (SRE) fundamentals: instrumentation, monitoring/alerting, incident response readiness, and post-incident improvement
• Embed privacy factors into design and delivery, ensuring GenAI solutions address PII/PHI handling, data residency, and safe logging/telemetry practices
• Operate within Scaled Agile Framework (SAFe), Lean, and Extreme Programming (XP) practices; contribute to sprint planning, story refinement, and technical acceptance criteria
• Mentor engineers, support technical onboarding, and contribute to interviewing and hiring
• Communicate tradeoffs, delivery status, and risks clearly; provide crisp technical recommendations aligned to business outcomes

Requirements

• 6+ years professional software engineering experience with modern full-stack delivery
• 3+ years building and deploying cloud-native solutions on AWS/Azure/GCP
• 1+ years hands-on experience delivering GenAI capabilities in products or internal platforms
• Prior experience with system design capability (distributed systems fundamentals, API-first design, scalability, resiliency, caching, data modeling, and security patterns)
• Prior experience with multiple of the following (depth in at least one primary stack): Angular and/or React, Node.js, Python, C#, .NET Core, Java, and/or Golang, SQL and NoSQL databases
• Prior experience with object-oriented programming (OOP), data structures/algorithms, secure coding, and performance considerations
• Prior experience driving quality through code reviews, automated testing, and clean engineering practices
• Prior experience with DevSecOps practices (CI/CD, branching strategies, automated testing, security scanning, quality gates)
• Prior experience with privacy/security engineering practices: PII classification, least privilege, encryption in transit/at rest, secrets handling, retention controls, and audit logging
• Prior experience with observability and operational readiness (logs/metrics/traces; incident practices where applicable)
• Prior experience integrating with one or more LLM providers (e.g., OpenAI, Anthropic Claude, Google Gemini) and applying appropriate usage patterns
• Prior experience with GenAI building blocks: Orchestration frameworks (e.g., LangChain and LangGraph or equivalent), Embeddings and vector databases, Prompt engineering and structured outputs, Practical evaluation approaches and basic guardrails
• Prior experience with Python proficiency for GenAI services, pipelines, and evaluation utilities
• Must be able to obtain US Government security clearance

Qualifications

• 6+ years professional software engineering experience with modern full-stack delivery, 3+ years building and deploying cloud-native solutions, 1+ years hands-on experience delivering GenAI capabilities

Skills

* Required skills