Technical Project Lead / Manager

Accenture Federal Services•Tampa, FL

18h

About The Position

At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward! Overview The Technical Project Lead / Manager will oversee the planning, delivery, and operational stability of cloud and on‑premises environments supporting advanced AI/ML workloads and high‑performance computing (HPC) systems. This role combines hands‑on technical leadership with project management responsibilities, ensuring that infrastructure, networking, CI/CD pipelines, and GPU‑accelerated compute environments meet mission and program objectives. The ideal candidate has strong experience with hybrid cloud architectures, HPC or GPU‑based environments, DevSecOps/CI‑CD automation, and Agile delivery frameworks. The Technical Project Lead will guide engineering teams, collaborate with stakeholders, and manage execution across multiple parallel workstreams.

Requirements

5 years of experience with any of the following knowledge:
Experience leading hybrid cloud and on‑premises infrastructure projects (AWS or private cloud).
Strong background in systems engineering, cloud engineering, or HPC engineering.
Hands‑on familiarity with GPU‑accelerated compute, containerized workloads, Kubernetes, and cluster‑based architectures.
Working knowledge of CI/CD pipelines and DevSecOps tooling.
Demonstrated ability to run Agile or hybrid‑Agile delivery processes.
Experience managing cross‑functional engineering teams and coordinating technical efforts.
Excellent communication skills with the ability to brief stakeholders and synthesize complex technical information.
An active TS/SI is required

Nice To Haves

Experience supporting AI/ML platforms, MLOps workflows, or data‑intensive systems.
Background with high‑speed networking (InfiniBand, data plane acceleration, or HPC fabrics).

Responsibilities

Lead the design, deployment, and optimization of cloud and on-prem compute environments supporting AI/ML, MLOps, and HPC workloads.
Oversee GPU-enabled compute clusters, HPC networking, and performance tuning.
Direct the implementation and maintenance of CI/CD pipelines supporting model training, model deployment, and data-intensive workflows.
Guide engineers on containerization, orchestration, system architecture, and infrastructure modernization.
Ensure systems comply with security, accessibility, and governance requirements (e.g., DevSecOps practices, hardened cloud/on-prem environments).
Own end-to-end delivery for infrastructure and engineering initiatives, including scope, schedule, risks, and dependencies.
Develop and maintain project roadmaps, resource plans, and technical execution milestones.
Drive a modified Agile delivery process tailored to the team’s engineering workflows, ensuring consistent cadence and continuous improvement.
Coordinate cross-functional contributors including cloud engineers, systems engineers, platform engineers, data engineers, and security professionals.
Monitor project health metrics and proactively escalate obstacles.
Facilitate technical reviews, sprint planning, backlog refinement, and stakeholder briefings.
Work directly with leadership, engineering teams, and mission/program stakeholders to align technical priorities and delivery timelines.
Translate complex technical requirements into clear work packages and implementation strategies.
Maintain strong relationships across internal teams and external partners supporting cloud, network, and AI/ML projects.
Oversee operational readiness, system reliability, and performance of hybrid compute environments.
Guide teams in implementing best practices for monitoring, logging, fault tolerance, and capacity management.
Partner with security teams to ensure compliance, secure configuration, and continuous risk management.
Support troubleshooting of complex infrastructure, networking, or performance issues across GPU and HPC platforms.