Lead Python Engineer for GenAI & ML Platforms

JPMorgan Chase; Plano (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorganChase in Plano, TX is seeking a Lead Software Engineer to drive design and delivery of GenAI-powered platforms in a fast-paced corporate technology environment.

You will lead an agile team spanning architecture, ML/AI enablement, and productionizing models, with emphasis on security, scalability, and reliability in financial services. The role requires deep Python/Java, microservices, Kubernetes, and experience delivering large-scale distributed systems.

Qualifications

• Formal training or certification in software engineering concepts and 5+ years applied experience.
• The successful candidate demonstrates deep distributed-systems engineering expertise in Python/Java plus strong platform, delivery, and production-operability discipline; Recent hands-on software development experience in large-scale distributed systems, primarily Python and modern microservices.
• Strong Python experience for AI/ML engineering, automation, model operationalization, and agentic AI services, including tool integration, monitoring, telemetry, and governance; Strong experience with REST APIs and service-oriented / microservices architecture
• 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
• Experience developing in Linux environments.
• Strong Kubernetes orchestration experience (building, deploying, and operating production services).
• Messaging expertise with Kafka, MQ, or similar platforms.
• Experience with backend infrastructure patterns (e.g., load balancing, autoscaling; Experience with NoSQL databases such as Cassandra; Experience with log analytics / observability tools (e.g., ELK, Splunk).
• Strong SDLC knowledge and agile ways of working, including CI/CD, application resiliency, security, testing, and operational stability; Strong communication skills and proven ability to influence across senior technology and business stakeholders.
• AI/ML platform exposure (MLOps, feature engineering, model hosting/operationalization; AWS and/or hybrid on-prem + cloud); Agentic AI experience: building and operating LLM-driven agents with tool integration, monitoring/telemetry, and governance/audit considerations.

Responsibilities

• Architect and implement resilient, scalable, fault-tolerant, low-latency services and drive target-state architecture.
• Design and deploy services that integrate with enterprise systems; ensure functional, performance, scalability, security, governance, and auditability requirements are met.
• Lead and mentor the development team in a high-pressured delivery environment; manage multiple deliverables across business groups and strengthen stakeholder relationships.
• Collaborate with LOB users, SMEs, architects, DBAs, and system administrators to design solutions, manage enhancements, and resolve issues.
• Build and mature capabilities that execute ML pipelines for fraud detection and risk assessment; support modeling teams in implementation and tooling.
• Productionalize models built by data scientists, including validation readiness and quality controls prior to live usage.
• Drives team adoption of enterprise-authored 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-authored AI-assisted development and automation capabilities, to improve the value realized by automation.
• Design and own reusable ML platform components (e.g., feature-store patterns, delivery pipelines) and establish monitoring/alerting for performance, scalability, availability, and reliability.
• Build agentic AI services to automate and enhance engineering and model-ops workflows (tool-using agents, orchestration, state management, and audit-ready traceability).
• Define and implement guardrails and evaluation approaches for agentic AI in production (quality, safety, latency, and cost).

Skills

Python

Java

Microservices

REST APIs

Kubernetes

AI/ML engineering

CI/CD

Security & governance

Distributed systems

Linux

MLOps

Agile / SDLC

Tools

Kafka

ELK

Splunk

Cassandra

Job description

JPMorganChase in Plano, TX is seeking a Lead Software Engineer to drive design and delivery of GenAI-powered platforms in a fast-paced corporate technology environment.

You will lead an agile team spanning architecture, ML/AI enablement, and productionizing models, with emphasis on security, scalability, and reliability in financial services. The role requires deep Python/Java, microservices, Kubernetes, and experience delivering large-scale distributed systems.