Lead Software Engineer - Python/Agentic AI/AWS at JPMC Candidate Experience page

Jersey City, New Jersey, United States -

Full Time

Start Date

Immediate

Expiry Date

15 Jun, 26

Salary

215000.0

Posted On

17 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Agentic AI, AWS, Generative AI, LLM Orchestration, System Design, APIs, SDKs, Terraform, AWS EKS, AWS ECS, CI/CD, Agile, Machine Learning Platforms, Data Engineering, Model Serving

Industry

Financial Services

Description

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Lead Software Engineer at JPMorganChase within Corporate Technology Chief Technology office, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. You will be joining our advanced optimization engineering team, driving innovation in AI-powered optimization across firmwide ML platforms. You will help shape the architecture, develop reusable APIs/SDKs, transform datasets and support AI/ML driven decision systems that improve cost efficiency and performance across heterogeneous environments. Job responsibilities * Design, build, and maintain scalable machine learning platforms and infrastructure to support end-to-end ML workflows * Design and develop Agentic AI based capabilities to analyze workloads and generate recommendations * Integrate data engineering, feature management, and model serving capabilities into unified ML platform solutions * Implement secure, high-quality production code for platform services, APIs/SDKs, and automation pipelines * Collaborate with data scientists, ML engineers, and product teams to understand requirements and deliver platform features that accelerate ML development and operations * Ensure platform reliability, scalability, and performance through proactive monitoring, troubleshooting, and continuous improvement * Produce architecture and design artifacts for platform components, ensuring alignment with enterprise standards and best practices * Automate infrastructure provisioning, configuration, and CI/CD pipelines for ML platform services * Contributes to software engineering communities of practice and events that explore new and emerging technologies * Adds to team culture of diversity, Opportunity, inclusion, and respect Required qualifications, capabilities, and skills * Formal training or certification on software engineering concepts and 5+ years applied experience * Experience in system design, application development, testing, and operational stability * Experience with Python (building APIs/SDKs) * Experience with Generative AI, specifically LLM Orchestration and Agentic AI libraries * Experience with cloud services (AWS S3, Lambda, Bedrock, Postgres), Infrastructure as Code (Terraform), and containerized application development (AWS EKS, ECS) * Comprehensive knowledge of the Software Development Life Cycle * Experience communicating to business facing customers and technical team Preferred qualifications, capabilities, and skills * Familiarity with AI-assisted development tools (GitHub Copilot, Anthropic Claude Code) * Knowledge of AI/ML model integration, context engineering and MCP * Exposure to Databricks or Snowflake * Familiarity with metrics processing tools (CloudWatch, Dynatrace, Datadog) * AWS certifications JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs [https://careers.jpmorgan.com/us/en/how-we-hire/faqs] for more information about requesting an accommodation. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

Responsibilities

The Lead Software Engineer will design, build, and maintain scalable machine learning platforms and infrastructure to support end-to-end ML workflows, including developing Agentic AI capabilities for workload analysis and recommendations. Responsibilities also involve integrating data engineering, feature management, and model serving into unified ML platform solutions while implementing secure, high-quality production code.