Forward Deployed Architect

What You Will Do

• Design the solution architecture for production-quality agentic AI systems end to end: Kubernetes deployment, agent runtimes, memory systems, orchestration, tool integration, and evaluation pipelines
• Set the reference architectures and engineering standards that Lead engineers build against, and hold the line on them through architecture review
• Architect data flywheels with AI Scientists that continuously improve agent quality through telemetry, benchmarking, automated evaluation, and structured feedback loops
• Embed security, guardrails, sandbox isolation, auditability, and policy enforcement directly into agent runtimes
• Drive disciplined build-versus-use decisions on open-source and third-party agent platforms
• Lead strategic AI programmes spanning several teams or functions and coordinate organisation-wide adoption across sites and business units
• Negotiate customer AI requirements, own key vendor and research partnerships, and grow Lead engineers into architecture and programme ownership
• Set the applied research agenda jointly with our AI Engineers, publish at least one Q1/Q2 journal paper each year, and represent SAIC as a technical voice externally.

What You Will Bring

• Strong programming skills in C++, Python, and CUDA or another GPU programming model, with a track record of production-quality, performance-critical software
• Proven experience designing and optimising high-throughput, low-latency systems, reasoning across software stacks, hardware capabilities, and system bottlenecks
• Deep HPC and AI infrastructure knowledge: benchmarking on large-scale clusters, GPUs, InfiniBand and Ethernet, RDMA, Kubernetes, and distributed storage
• Track record leading complex, multi-workstream AI or software programmes with accountability for architecture, schedule, and technical risk
• Recognised depth in two or more AI domains, with demonstrated ability to set engineering standards and grow Lead-level engineers
• Agile delivery leadership at programme level, including the ability to operate in a Scrum Master capacity and align multiple teams to a common plan
• Credibility with senior client and partner stakeholders, and the ability to influence a technical decision you do not control

Qualifications

Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field, with more than five (5) years in an AI-focused role and demonstrated ability to lead projects and mentor team members.

Nice to Have

Experience in regulated industries including but limited to government, finance, or healthcare; background in AI policy, cybersecurity, and compliance frameworks; patents, standards body participation, or conference programme committee service; experience building an engineering practice or function from an early stage; established working relationships with platform and hardware vendors or with academic research groups.