We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology, specifically as a part of the Big Data Platforms team, you will play a crucial role in an agile team committed to enhancing, creating, and delivering high-quality technology products in a secure, stable, and scalable manner. Your role as a vital technical contributor will involve developing critical technology solutions across numerous technical domains within various business functions, all aimed at supporting the firm's business goals.

You will be joining our advanced optimization engineering team, driving innovation in AI-powered compute optimization. This role will play a pivotal part in building scalable services and intelligent automation for optimizing large-scale data workloads running on cloud platforms like AWS EKS, AWS EMR, Databricks and Snowflake.

You will help shape the architecture, develop reusable SDKs, transform datasets and support AI/ML driven decision systems that improve cost efficiency and performance across heterogeneous environments.

Job responsibilities

Execute creative software solutions, including design, development, and technical troubleshooting, with the ability to think beyond conventional approaches to build solutions or resolve technical problems Develop secure, high-quality production code, and review and debug code written by others Identify opportunities to eliminate or automate the remediation of recurring issues to enhance the overall operational stability of software applications and systems Lead evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented assessments of architectural designs, technical credentials, and their applicability within existing systems and information architecture Lead communities of practice across Software Engineering to promote awareness and adoption of new and leading-edge technologies Contribute to a team culture of diversity, equity, inclusion, and respect Develop and deploy cloud infrastructure platforms that are secure, scalable, and optimized for AI and machine learning workloads Collaborate with AI teams to understand computational needs and translate these into infrastructure requirements Monitor, manage, and optimize cloud resources to maximize performance and minimize costs Design and implement continuous integration and delivery pipelines for machine learning workloads Develop automation scripts and infrastructure as code to streamline deployment and management tasks

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience Hands-on practical experience in system design, application development, testing, and operational stability Advanced proficiency in one or more programming languages such as Python and/or Java Experience with AI/ML model integration, prompt engineering, or LLM APIs (OpenAI, Bedrock) Experience with AWS services (S3, EKS, Step Functions, Lambdas, RDS, API GW) Strong understanding of containerization and orchestration using Docker and Kubernetes Familiarity with data processing frameworks such as Apache Spark or Flink Experience building RESTful APIs and working with event-driven or serverless architectures Proficiency with Git, CI/CD pipelines, Terraform and automated testing frameworks Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

Preferred qualifications, capabilities, and skills

Exposure to Snowflake, Databricks, EMR, or related data platforms Familiarity with metrics processing tools (CloudWatch, Dynatrace, Datadog)