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


* Proficiency in architecting software solutions at scale - you've designed systems that other teams depend on


* Self-directed and autonomous: you drive to outcomes without waiting for direction


* Strong client-facing communication skills, effective across time zones in a distributed team


* Deep knowledge of AWS and cloud-based infrastructure


* Track record building res...