Job description

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 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 GitHub 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 SDLC • Actively 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, EventBridge, SageMaker, 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, including but not limited to: Step Functions, Lambda, ECS/EKS, SageMaker, Bedrock, Glue, EventBridge, and IAM • Proficiency in Terraform for infrastructure-as-code, including module development, state management, and multi-environment deployment patterns • Experience with GitHub Copilot and AI-assisted development workflows; ability to evaluate, govern, and scale AI coding tools within an engineering team • Ability to independently tackle complex design and functionality problems with minimal oversight , driving solutions from ambiguous requirements to production • Practical cloud-native experience with strong understanding of security, scalability, resilience, and cost optimization in AWS • Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance/ways of working (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs. • Strong understanding of responsible AI use in engineering workflows , including data sensitivity considerations, resiliency/security implications, and control expectations; ability to coach managers/leads and influence leaders on safe scaling patterns. • Preferred qualifications, capabilities, and skills • Familiarity with SQL, Bash, or TypeScript/JavaScript • Hands on experience developing in Java, or Golang Be an integral part of an agile team constantly pushing the envelope to enhance, build, and deliver top-notch technology products

Requirements

Must-haves

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
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 GitHub 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 SDLC
Actively 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
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, including but not limited to: Step Functions, Lambda, ECS/EKS, SageMaker, Bedrock, Glue, EventBridge, and IAM
Proficiency in Terraform for infrastructure-as-code, including module development, state management, and multi-environment deployment patterns
Experience with GitHub Copilot and AI-assisted development workflows; ability to evaluate, govern, and scale AI coding tools within an engineering team
Ability to independently tackle complex design and functionality problems with minimal oversight , driving solutions from ambiguous requirements to production
Practical cloud-native experience with strong understanding of security, scalability, resilience, and cost optimization in AWS
Familiarity with SQL, Bash, or TypeScript/JavaScript
Hands on experience developing in Java, or Golang
Be an integral part of an agile team constantly pushing the envelope to enhance, build, and deliver top-notch technology products

Nice-to-haves

Preferred qualifications, capabilities, and skills

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

agileaimlawsazuregcpci/cdpythonsqltypescriptjavascriptjavagolang

Platform: oracle-cloud
Effort: medium