Lead Software Engineer - AWS, Python, AI/ML

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 Consumer and Community Bank, you 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

• Designs, builds, and operates AWS-native service engineering solutions, including automated provisioning, configuration management, and lifecycle orchestration (IaC, CI/CD, self-service workflows), applying creative problem-solving to break down complex distributed-systems issues beyond conventional approaches.
• Develops secure, resilient, production-grade automation and agentic AI solutions (LLM-based agents integrated with cloud services and enterprise systems), maintaining high-quality code, algorithms, and event-driven/run-time workflows that operate reliably with dependent platforms and control planes.

• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.

• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems

• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies

• Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification in software engineering concepts and 5+ years applied experience

• experience building AWS-based service engineering, provisioning, and automation solutions.
• Hands-on experience designing and delivering cloud-native systems (infrastructure + applications), including IaC-driven provisioning, CI/CD, testing, observability, and operational stability (SRE/operations mindset).
• Proficient in one or more modern programming languages used for automation and cloud services, including developing agentic AI integrations where applicable.

• Familiarity with agentic workflows and frameworks (e.g., LangChain, LangGraph, Auto-GPT)

• Experience integrating AI/ML techniques into software systems, including familiarity with LLMs, Generative AI, NLP, RAG, AI evals and coding assistants

• Managing and mentoring software engineering or AI/ML teams, with experience as a hands-on practitioner delivering production-grade solutions

• Good understanding of data structures, algorithms, and practical machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn)

• Advanced proficiency in Java or Python for software system development; strong grasp of software engineering best practices, system design, application development, testing, and operational stability

• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.

• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

Preferred qualifications, capabilities, and skills

• Experience working at code level with advanced AI/ML business applications (e.g., LLMs, Generative AI, NLP)

• AWS Certifications (Solution Architect Associate or Professional) are advantageous

• In-depth knowledge of the financial services industry and their IT systems

• Practical cloud native experience