Product Engineering | PxE Platforms | Group Engineering Leader

Engineering Leader
Role Summary
Lead a full-stack engineering workstream delivering cloud-native products and Generative AI (GenAI) capabilities. You will guide day-to-day technical execution, ensure secure and reliable delivery, and partner with product, design, and stakeholders to translate requirements into working software-while incorporating strong system design and privacy-by-design practices.
Recruiting for this role ends on 5/31/2026
Key Responsibilities

Workstream leadership: Own delivery for an engineering workstream (scope, plan, dependencies, risks), coordinating across engineers, product, QA, and platform/security partners.
System design & architecture: Produce and socialize system designs (component diagrams, sequence flows, data flows, scalability/resiliency patterns, failure modes), and drive design reviews and technical tradeoffs.
Hands-on full-stack delivery: Design and build front-end and back-end components; review code, improve test coverage, and drive pragmatic engineering standards.
GenAI implementation: Deliver GenAI features using patterns like Retrieval Augmented Generation (RAG), prompt design, tool/function calling, and agent-style workflows.
Agent orchestration with LangGraph: Build and maintain multi-step GenAI workflows using LangGraph (stateful execution, routing, tool use, human-in-the-loop patterns), including traceability and evaluation.
Cloud-native engineering: Build and operate solutions on AWS, Azure, and/or Google Cloud Platform (GCP) using Platform as a Service (PaaS), Functions as a Service (FaaS), containers, and microservices.
DevSecOps execution: Implement continuous integration/continuous delivery (CI/CD), quality gates, security scanning, and release practices using tools such as Azure DevOps (ADO) and/or GitHub, plus static analysis tools (e.g., SonarQube).
Reliability & operations: Apply Site Reliability Engineering (SRE) fundamentals-instrumentation, monitoring/alerting, incident response readiness, and post-incident improvement.
Privacy & data protection: Embed privacy factors into design and delivery (data minimization, purpose limitation, retention, consent/notice where applicable, access controls, encryption, secrets management, auditing). Ensure GenAI solutions address PII/PHI handling, data residency needs, and safe logging/telemetry practices.
Agile delivery: Operate within Scaled Agile Framework (SAFe), Lean, and Extreme Programming (XP) practices as applicable; contribute to sprint planning, story refinement, and technical acceptance criteria.
Coaching & team development: Mentor engineers, support technical onboarding, and contribute to interviewing and hiring.
Stakeholder communication: Communicate tradeoffs, delivery status, and risks clearly; provide crisp technical recommendations aligned to business outcomes.
Qualifications
Required (full stack & system design)

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 (grounding, input/output controls, safety filters)
Prior experience with Python proficiency for GenAI services, pipelines, and evaluation utilities.
Must be able to obtain US Government security clearance.
Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $ 144,300 to $ 296,100.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
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