We’re looking for a tech leader ready to take their career to new heights. Join the ranks of top talent at one of the world’s most influential companies.
As a Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking Machine Learning Intelligence Operations, 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
- Collaborate with cross-functional teams, integrating partners, and key stakeholders to align on requirements, resolve dependencies, and ensure successful end-to-end project rollout
- Experienced and skilled in using Terraform for infrastructure deployment; familiarity with EAC is an added advantage
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Drives decisions that influence the product design, application functionality, and technical operations and processes
- Hands-on experience with any Large Language Models, including making API calls, handling streaming responses (SSE/WebSocket), and managing end-to-end request lifecycle
- General understanding of LLM performance considerations, including response latency, token usage and cost implications, and approaches to evaluating model output quality
- Proficiency in prompt engineering techniques, including context window management, token budgeting, and applying foundational LLM use cases
- Leverage Amazon Bedrock for model invocation and work alongside supporting AWS services
- Familiarity with Agentic AI concepts
- Actively contributes to the engineering community as an advocate of firm-wide frameworks, tools, and practices of the Software Development Life Cycle
- Influences peers and project decision-makers to consider the use and application of leading-edge technologies
- Adds to the team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in one or more programming language(s) (Java, Python)
- Practical AWS cloud native experience
- Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., AI/ML, UI development, mobile development etc.)
- Ability to tackle design and functionality problems independently with little to no oversight
- Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field
Preferred qualifications, capabilities, and skills
- Hands on experience with GenAI and AI Agents
- Proficient and hands On with Terraform for Infrastructure Deployment and knowledge of EAC is a plus
- Proficient and hands on with AWS Container Orchestration Services like ECS and EKS.
- Experience with ML Engineering
- Extensive experience with Amazon Web Services (AWS), including deploying, managing, and scaling applications using services such as EC2, S3, Lambda, and RDS
- Proficiency in AWS security best practices and cost optimization strategies