Principal Engineer Senior Manager

Accenture Federal Services•Washington, DC

2d•$177,900 - $203,600

About The Position

The Senior Principal Engineer Manager at Accenture Federal Services (AFS) is a top-tier technical leadership role. This position sits at the intersection of enterprise architecture, mission-critical delivery, and hands-on innovation. You aren't just managing people; you are the "engineer's engineer," responsible for the technical integrity of massive federal systems that impact millions of citizens. As a Principal Engineer, you will serve as the primary technical authority for high-stakes federal engagements. You will bridge the gap between abstract mission goals and concrete, high-performance codebases.

Requirements

10+ years software development
8+ years full stack (back end: Java/Python; front end: Angular/React; data: SQL and NoSQL, cloud: AWS)
5+ years developing, testing, and launching production software in big tech or startup environments
3+ years leading product architecture and complex technical design
1+ years building AI enabled product features and/or using AI to improve delivery (AI coding tools, intelligent analytics)
Bachelor’s degree in Computer Science, Engineering, or a related technical field (4 additional years of experience may be substituted)
U.S Citizenship

Nice To Haves

Advanced Degree
Motivated and proactive, with a desire to understand and address complex areas
Curiosity for learning about new technology, industry best practices, and areas of risk, analyzing and turning new insights into concrete action
Commitment to delivering tangible outcomes for customers and stakeholders
Strong written and verbal communication/interpersonal skills to effectively collaborate with cross-functional teams and stakeholders

Responsibilities

Define a product level technical vision aligned to customer outcomes and client goals.
Establish lightweight architectural guardrails (interfaces, patterns, conventions) that enable rapid iteration with quality.
Use business, user, and operational signals to prioritize for accelerated time to value.
Design and integrate AI capabilities where possible with clear interfaces, guardrails, and observability to ensure reliable, safe, and measurable user value.
Convert strategy into technical roadmaps, sequencing work by impact, effort, risk, and learning value.
Manage the complete product delivery lifecycle, encompassing conceptualization, development, launch, and iterative enhancement, with a focus on reducing cycle time and accelerating delivery.
Write product code and tests across the stack (e.g., back end Java/Python, front end React/Angular, data SQL/NoSQL).
Govern multiple product codebases; set measurable objectives and maintain code quality, engineering throughput, and release predictability.
Leverage AI tools for code generation, test authoring, defect triage, and documentation to shorten feedback loops, reduce cycle time, and improve developer throughput.
Establish domain driven modularity by defining bounded contexts, enforcing separation of concerns, and composing services/components to enable rapid iteration and safe refactoring.
Design APIs and contracts with stable, versioned REST interfaces, schemas and ensure backward compatibility and protect integrations through contract testing.
Model data and integrity via pragmatic relational/NoSQL schemas; enforce referential integrity and validation; plan sensible indexing and migration strategies.
Engineer for performance and scale using caching, pagination, batching, and concurrency controls; set performance budgets and profile regularly.
Design cloud native products with modular, scalable microservices and event driven patterns and clear contracts (REST/streaming/batch).
Standardize containers and orchestration by building images and operating containers with simple, repeatable deployment paths.
Implement data and streaming foundations using SQL/NoSQL models, caching tiers, and Kafka/Pub/Sub to deliver low latency, high throughput experiences.
Run CI/CD at speed with trunk-based development, automated tests, and progressive delivery (feature flags, blue green) to shorten feedback loops and reduce risk.
Set standards for clarity, reliability, performance, security, and observability; embed modern SDLC practices (DevSecOps, trunk based development, feature flags, AI coding tools).
Serve as a primary technical authority and mentor; lead design reviews, improve documentation, and champion reusability for efficiency.
Provide concise, data driven updates on status, risks, trade offs, and decisions to executives and cross functional leadership.
Build confidence via transparent communication, disciplined execution, and fast, measurable results.
Iterate based on telemetry, experiment outcomes, and customer feedback; institutionalize learning and best practices.
Activate growth levers (new user flows, platform reuse, developer experience gains) to increase user value and engineering throughput.