Qualifications Required: + 7+ years of experience in software, systems, or embedded engineering + 7+ years of experience working in Java/J2EE + 7+ years of experience developing or deploying AI solutions, custom hardware, or high-performance platforms + 7+ years of experience with Linux internals, device drivers, and kernel or embedded systems programming + Experience in C/C++ and Python + 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. + 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 The team AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure.