Senior AWS Engineer - ML

Testing Site - JPMC; Houston (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

JPMorganChase in Houston seeks a Senior Lead Data Engineer to join an agile team delivering trusted market-leading technology products in a secure, scalable way. You will provide technical guidance, own critical data pipelines, and drive DevOps practices, with emphasis on AWS, Python, ML, and MLOps.

The role requires strong collaboration with stakeholders and a track record of delivering production-grade solutions.

Qualifications

• Formal training in software engineering concepts and 10+ years of applied experience.
• Extensive experience building and operating AWS/public cloud-based applications.
• Strong Python programming skills.
• Proven hands-on delivery across system design, application development, testing, and operational stability.
• Proficiency in automation, CI/CD, and all aspects of the SDLC.
• Experience with pipelines and DAGs for data processing and/or machine learning.
• Demonstrated proficiency in cloud and AI/ML software practices.
• Strong problem-solving, communication, and stakeholder collaboration skills.
• Familiarity with MLOps practices and tooling.
• Experience driving adoption of AI engineering tools (e.g., GitHub Copilot) for JIRA, documentation, coding, and releases, with measurable productivity and quality gains.

Responsibilities

• Provides technical guidance to business teams, contractors, and vendors.
• Develops secure, high-quality production code and reviews others' code.
• Drives decisions influencing product design, functionality, and operations.
• Acts as a function-wide subject matter expert in one or more focus areas.
• Contributes to the engineering community with firmwide SDLC frameworks, tools, and practices.
• Influences peers on adoption of leading-edge technologies.
• Adds to team culture of diversity, inclusion, and respect.

Skills

Python programming

AWS cloud

CI/CD automation

Data processing pipelines

Machine Learning concepts

MLOps practices

SDLC knowledge

Problem solving

Education

Formal training in software engineering concepts

Tools

Terraform

GitHub Copilot

Airflow

Kubernetes

Docker

MLflow

Datadog

Dynatrace

Job description

Be an integral part of an agile team that is constantly pushing the envelope to enhance, build, and deliver top‑notch technology products.

As a Senior Lead Data Engineer at JPMorganChase within the Commercial and Investment Banking, 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

• 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
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firmwide 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 in software engineering concepts and 10+ years of applied experience.
• Extensive experience building and operating AWS/public cloud-based applications.
• Strong Python programming skills.
• Proven hands-on delivery across system design, application development, testing, and operational stability.
• Proficiency in automation, CI/CD, and all aspects of the SDLC.
• Experience with pipelines and DAGs for data processing and/or machine learning.
• Demonstrated proficiency in cloud and AI/ML software practices.
• Strong problem-solving, communication, and stakeholder collaboration skills.
• Familiarity with MLOps practices and tooling.
• Experience driving adoption of AI engineering tools (e.g., GitHub Copilot) for JIRA, documentation, coding, and releases, with measurable productivity and quality gains.

Preferred qualifications, capabilities, and skills

• Experience leading a small team as tech lead and/or manager.
• Proficiency with AWS (hands-on): SageMaker, Bedrock, Glue, Redshift Serverless, DynamoDB, EventBridge, Step Functions, Lambda, ECS, EKS, Kinesis, CloudWatch
• Experience with Python, Terraform, GitHub Copilot, Airflow, Kubernetes, Docker, MLflow, Datadog, Dynatrace, MCP.
• Familiarity with JPMC platforms/tools (highly preferred): Jules/JET, GKP (Gaia Kubernetes), Fusion MLOps