Senior Lead Software Engineer - Python, Golang, Java

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 JPMorgan

Chase within the Corporate Sector - CFS Cloud Enablement Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities

Provides authoritative technical guidance and architectural direction to business stakeholders, technical teams, contractors, and vendors — with a focus on workflow automation, AI/ML platforms, and cloud-native solutions on AWS, Azure and GCP.Designs, engineers, and implements end-to-end workflow automation solutions and AI/ML pipelines, from architecture through production deployment

Develops secure, high-quality production code; reviews, debugs, and optimizes code written by others — leveraging Git Hub Copilot and AI-assisted development practices to accelerate delivery

Drives architectural decisions that influence product design, application functionality, and technical operations — including infrastructure-as-code standards using Terraform across AWS environments

Serves as a function-wide subject matter expert in AWS cloud architecture, MLOps, workflow orchestration, and intelligent automation

Defines and enforces best practices for CI/CD pipelines, IaC (Terraform), model lifecycle management, and automated testing within the SDLCActively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices — championing AWS Well-Architected principles, Terraform module reuse, and responsible AI/ML governance

Influences peers and project decision-makers to evaluate and adopt leading-edge technologies including LLMs, agentic AI frameworks, and cloud-native automation services (e.g., AWS Step Functions, Event Bridge, Sage Maker, Bedrock)
Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establishes measurable expectations (e.g., throughput, defect reduction, reliability) and ensures consistent validation, security, resiliency, and reuse of proven patterns.

Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets. Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establishes measurable expectations (e.g., throughput, defect reduction, reliability) and ensures consistent validation, security, resiliency, and reuse of proven patterns.

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 10+ years applied experience

Hands-on practical experience delivering system design, application development, testing, and operational stability — with demonstrated delivery of production-grade AI/ML and automation solutions

Advanced proficiency in Python Advanced knowledge of AI/ML frameworks and tooling and their operationalization in cloud environments

Deep expertise in AWS cloud services relevant to automation and AI/ML workloads,…