Sr Lead Software Engineer - AWS - Lead AI/ML Platform Engineer

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorganChase within the Firmwide AI/ML Deployment Platform team, you are an integral part of a globally distributed team — spanning Glasgow, London, New Jersey, and India — that works to architect, build, and own the infrastructure that makes model deployment work at scale. You'll operate with significant autonomy: owning technical direction, engaging directly with US-based clients, and making architectural decisions with real production consequences. We build the control plane, APIs, monitoring, and deployment infrastructure that internal teams depend on. The platform is always evolving — new regions, new failure modes, new scale requirements. If you like owning problems end-to-end, making hard tradeoffs, and shipping systems that other engineers build on top of, you'll fit in.

Job responsibilities

• Drive architectural vision for platform components: control plane integration, multi-region deployment, and disaster recovery

• Design and implement APIs for retraining, scheduling, endpoint deployment, and autoscaling

• Build infrastructure for seamless integration across control plane and client accounts

• Engage directly with US-based clients — requirements, strategic solutioning, and debugging

• Make independent architectural decisions and own technical tradeoffs with minimal oversight

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors

• Drives decisions that influence the product design, application functionality, and technical operations and processes

• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.

• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.

Required Qualifications, Capabilities, and Skills

• Formal training or certification on software engineering concepts and 5+ years applied experience

• Industry experience as a platform engineer, leading large-scale platform infrastructure delivery

• Deep AWS expertise covering networking (VPCs, DNS, cross-account connectivity, service mesh), scalability, multi-account architectures, and security