Product Engineering Group Engineering Leader

About This Role

Lead a full-stack engineering workstream delivering cloud-native products and Generative AI capabilities. Guide day-to-day technical execution, ensure secure and reliable delivery, and partner with stakeholders to translate requirements into working software.

Responsibilities

• Own delivery for an engineering workstream including scope, plan, dependencies, and risks, coordinating across teams.
• Produce and socialize system designs, driving design reviews and technical tradeoffs.
• Design and build front-end and back-end components, review code, and improve test coverage.
• Deliver GenAI features using patterns like Retrieval Augmented Generation (RAG), prompt design, 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 GCP using PaaS, FaaS, containers, and microservices.
• Implement continuous integration/continuous delivery (CI/CD), quality gates, and security scanning practices.
• Apply Site Reliability Engineering (SRE) fundamentals including instrumentation, monitoring, and incident response.
• Embed privacy factors into design and delivery, ensuring GenAI solutions address PII/PHI handling and safe logging.
• Operate within Agile frameworks, contributing 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, providing crisp technical recommendations.
• 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 (grounding, input/output controls, safety filters).

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 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).
• 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 cloud-native solutions, and 1+ years delivering GenAI capabilities.

Nice to Have

• 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.

Skills

* Required skills