Senior Lead AI Platform Engineer (Python, ML, Cloud)

Socket.dev; Plano (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorganChase is seeking a Senior Lead Software Engineer within Corporate Technology - Chief Technology Office to lead end-to-end delivery of AI-enabled platform components. You will design scalable architectures, own production services, and mentor engineers in a fast-paced agile environment.

Role emphasizes hands-on Python, API/SDK development, and collaboration with data scientists and product teams to drive measurable outcomes, with a focus on reliability, performance, and cost efficiency.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Strong hands-on depth in Python, including building and maintaining APIs/SDKs; ability to lead design and perform high-quality code/design reviews.
• Experience with enterprise-authorized AI-assisted development tools (e.g., GitHub Copilot, Claude Code) and establishing practical team norms for validation and quality.
• Experience delivering platforms involving Generative AI, including LLM orchestration patterns and agentic AI frameworks, with production-grade evaluation and monitoring practices.
• Practical experience with AWS, containerized platforms (EKS/ECS), and Terraform (or equivalent IaC).
• Databricks experience building/operating data/ML workloads (pipelines, notebooks/jobs, Delta/feature datasets).
• SDLC, agile delivery, CI/CD, and modern engineering quality controls.
• Strong communication with business-facing partners and technical stakeholders; translate strategy into execution.

Responsibilities

• Serves as a hands-on technical leader, contributing production code (primarily Python) and owning end-to-end delivery from design through production operations.
• Leads system and platform architecture for components supporting end-to-end ML workflows, including data transformation patterns, feature management integration, orchestration enablement, and model serving integration.
• Designs and develops agentic AI capabilities that analyze workloads and generate optimization recommendations, including evaluation approaches, monitoring, and feedback loops for production readiness.
• Builds and maintains reusable APIs/SDKs and reference implementations that enable consistent platform adoption and reduce duplicated effort across teams.
• Partners with data scientists, ML engineers, and product teams to clarify requirements, define technical approaches, manage dependencies, and deliver measurable outcomes.
• Ensures platform reliability, scalability, performance, and cost efficiency through SLOs, proactive monitoring, incident response participation, root-cause analysis, and continuous improvement.
• Automates infrastructure provisioning, configuration, and CI/CD pipelines for platform services using Infrastructure as Code, promoting safe and repeatable deployments across environments.
• Drives adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, establishing consistent validation standards (correctness, performance, security) and promoting reuse of effective patterns.
• Produces architecture and design artifacts for platform components, ensuring alignment with enterprise standards and best practices.
• Mentors engineers through technical coaching, design reviews, and pairing, contributing to a strong culture of engineering excellence.
• Contributes to software engineering communities of practice and events that explore new and emerging technologies.

Skills

Python

System design

AWS

CI/CD

Databricks

IaC/Automation

LLM/Generative AI

Communication

Leadership

APIs/SDKs

Tools

GitHub Copilot

Claude Code

Terraform

Databricks

Kubernetes (EKS/ECS)

Job description

JPMorganChase is seeking a Senior Lead Software Engineer within Corporate Technology - Chief Technology Office to lead end-to-end delivery of AI-enabled platform components. You will design scalable architectures, own production services, and mentor engineers in a fast-paced agile environment.

Role emphasizes hands-on Python, API/SDK development, and collaboration with data scientists and product teams to drive measurable outcomes, with a focus on reliability, performance, and cost efficiency.