Senior
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
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