Java Full Stack Developer-Software Engineer III

Deloitte•Atlanta, GA

2d•Onsite

About The Position

Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Software Engineer III- Sr. Java Full Stack Developer you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite client service delivery. Join our AI and Systems Co-Design team, pioneering high-performance software and hardware technologies for AI and next-generation consumer devices. As a Consultant, you’ll help design, build, and optimize foundational tools and applications that power cutting-edge AI platforms and smart devices. You’ll collaborate cross-functionally, tackle large-scale technical challenges, and deliver innovative solutions with global impact.

Requirements

Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeanor
Ability to meet deadlines
Ability to provide clear guidance to others
6+ years of experience in software, systems, or embedded engineering.
6+ years of experience working Java/J2EE.
6+ years of experience developing or deploying AI solutions, custom hardware, or high-performance platforms.
6+ years of experience with Linux internals, device drivers, and kernel or embedded systems programming.
Proficient in C/C++ and Python; familiarity with Go or Rust a plus.
Strong understanding of AI/ML frameworks (PyTorch, TensorFlow, ONNX) and performance/model optimization.
Familiarity with hardware-software co-design (ASICs, FPGAs, or SoCs).
Demonstrated skill in performance profiling, benchmarking, and system tuning.
Knowledge of distributed systems, cloud/edge computing, and containerization (Docker, Kubernetes).
Understanding of network protocols, security best practices, and scalable API design.
Experience with Git, CI/CD pipelines, and modern DevOps practices.
Experience working within Agile/Scrum development teams, participating in sprint planning, code reviews, and collaborative solutioning.
Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience.
Limited immigration sponsorship may be available.
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve.

Nice To Haves

Experience developing or deploying AI solutions, custom hardware, or high-performance platforms.
Proven ability to communicate complex technical concepts clearly and effectively.
Analytical ability to manage multiple projects and prioritize tasks into manageable work products
Can operate independently or with minimum supervision.
Excellent Written and Communication Skills.
Ability to deliver technical demonstrations.

Responsibilities

Design, develop, and optimize scalable software for AI platforms and consumer devices.
Integrate and automate load, stress, and real-user scenario testing into the development and production lifecycle.
Analyze, monitor, and address performance, reliability, and scalability challenges in complex systems.
Collaborate with engineers working on custom hardware, embedded systems, and cloud infrastructure.
Apply advanced profiling, benchmarking, and system optimization techniques.
Contribute to solution architecture, API design, security, and system integration.
Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management.
Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes.