Lead Software Engineer - Java/Python/AWS/AI/LLM
Salary not listed • Plano, TX, United States • Full-time
Posted 7d ago
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Job Location
Plano, TX, United States
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
LLM Engineer
About the job
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 JPMorganChase within the Consumer & Community Banking, OPS Tech, 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. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Responsibilities
- Design and develop full-stack software solutions using innovative approaches aligned to business outcomes.
- Build and implement AI-driven capabilities, including LLM-based services, orchestration, and integrations into business workflows.
- Architect and deliver cloud-native microservices and APIs with strong security controls, scalability, resilience, and performance.
- Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, while establishing consistent validation standards and promoting reuse of effective patterns.
- Mentor and develop engineers through code reviews, pairing, technical guidance, and feedback.
- Establish and own engineering standards across the team (architecture patterns, coding standards, testing strategy, operational readiness).
- Define and operate service reliability practices (SLIs/SLOs, incident response, root-cause analysis, postmortems, and continuous reliability improvements).
- Identify recurring operational issues and automate remediation to improve system stability and observability (logs/metrics/tracing).
- Build and maintain CI/CD pipelines and release strategies to enable safe, predictable delivery.
- Communicate status and risks clearly; manage priorities and dependencies across multiple initiatives; collaborate in a Scrum team and participate in Agile ceremonies.
- Deliver production code primarily in Java (and Python as needed) using AWS (e.g., ECS) and related technologies.
Requirements
- Formal training or certification in Software Engineering and 5+ years of applied experience building production systems.
- Strong system design, application development, and operational stability skills in production environments (including on-call/incident ownership).
- Expertise designing and building microservices and RESTful APIs, with strong knowledge of data technologies and integration patterns.
- Hands-on experience building cloud-native systems on at least one major cloud platform (AWS, GCP, or Azure).
- Experience with distributed systems concepts (scalability, resiliency, concurrency, idempotency, failure modes, and performance tuning).
- Proven ability to influence product design and technical direction by proposing pragmatic architectures, tradeoffs, and standards aligned to firm SDLC, security, and controls expectations.
- Hands-on experience using enterprise-authorized AI-assisted software development tools, with demonstrated ability to evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
- Demonstrated experience leading effective team use of approved AI-assisted development practices (coding, code review, test acceleration, troubleshooting), including setting expectations and reusable validation patterns.
- Hands-on experience with Large Language Models (LLMs) and generative AI use cases (e.g., RAG, summarization/extraction, workflow assistants), including evaluation and monitoring considerations.
- Understanding of responsible AI use in engineering workflows (data sensitivity, safe handling of inputs/outputs, resiliency/security expectations) and ability to guide peers on safe and effective usage.
- Strong communication and stakeholder management skills; ability to deliver across multiple initiatives and drive outcomes through ambiguity.