As a Applied AI/ML Lead Engineer in our Applied AI ML - Python & Agentic AI team, you will design, build, and productionize Generative AI and Agentic AI solutions. The ideal candidate brings a balanced mix of modern AI/ML delivery (LLMs/SLMs, RAG, tool-using agents, evaluation, MLOps) and backend/service engineering (Java and/or Python, APIs/microservices, testing, CI/CD, observability, reliability) on AWS and cloud-native platforms.
This role values modern AI engineering workflows and tooling such as GitHub Copilot and Claude Code to accelerate delivery while maintaining quality and security. Familiarity with MCP (Model Context Protocol), Agent Skills and designing agentic systems that integrate models with tools and enterprise data via structured interfaces is a plus.
Job Responsibilities
- Design, develop, and deploy GenAI and Agentic AI solutions that improve automation, decision-making, and user experience across business workflows.
- Build LLM/SLM-powered applications including RAG-based systems, summarization/extraction pipelines, chat/coplay experiences, and tool-using agents.
- Engineer production-grade services using Java and/or Python (REST/gRPC APIs, microservices, libraries), following secure coding and reliability best practices.
- Develop prompt strategies and prompt engineering assets (templates, routing, guardrails), and implement automated evaluation to improve quality over time.
- Build and maintain data pipelines and processing workflows required for ML/GenAI use cases using cloud services.
- Apply MLOps practices across the lifecycle: experimentation, versioning, CI/CD, deployment, monitoring, and maintenance for models/prompts/agents.
- Implement robust testing (unit/integration), performance benchmarking (latency/cost), and observability (logging/metrics/tracing) for AI services.
- Collaborate with cross-functional stakeholders to define requirements, success metrics, and rollout plans; communicate complex topics clearly to technical and non-technical audiences.
- Strong problem-solving skills and ability to work effectively in ambiguous environments with multiple stakeholders.
Required Qualifications, Capabilities, and Skills
- Undergrad or Master’s degree (or equivalent practical experience) in Computer Science, Data Science, Machine Learning, or related field.
- Hands-on experience building applied AI/ML or GenAI solutions (e.g., RAG, classification, extraction, ranking, summarization, copilots).
- Familiarity with MCP (Model Context Protocol), Agent Skills and architectures that connect models to tools/data through standardized interfaces.
- Familiarity with LLM application patterns: embeddings/vector search, prompt orchestration, tool calling/function calling, safety/guardrails, evaluation.
- Strong software engineering experience delivering production systems; ability to design maintainable architectures and write clean, testable code.
- Proficiency in Java and/or Python and experience building APIs/services and integrating with data sources and downstream systems.
- Experience deploying solutions on AWS and cloud-native environments; understanding of security fundamentals and operational excellence.
- Experience with modern engineering practices: CI/CD, code reviews, unit testing (e.g., pytest/JUnit), and deployment automation.
- Experience with containers and orchestration (e.g., Docker, Kubernetes/EKS) and production monitoring practices.
Preferred Qualifications, Capabilities, and Skills
- Experience building agentic AI systems (multi-step workflows, tool routing, planning, memory patterns, supervision/fallback strategies).
- Experience with AWS Bedrock and/or SageMaker (or equivalent managed ML/GenAI platforms) and deployment patterns for scalable inference.
- Experience with evaluation frameworks and approaches (golden datasets, LLM-as-judge, human-in-the-loop review, red teaming).
- Experience fine-tuning models (e.g., LoRA/QLoRA/DoRA) and/or working with SLMs, embeddings, and retrieval systems.
- Experience with developer productivity tooling such as GitHub Copilot and Claude Code, paired with strong SDLC controls.
- Knowledge of the financial services industry and operating in regulated environments (auditability, controls, data handling).
- Exposure to distributed compute/training concepts (e.g., DDP, sharding) and performance/cost optimization.
Skills Required
- Undergraduate or master's degree, or equivalent practical experience, in Computer Science, Data Science, Machine Learning, or a related field
- Hands-on experience building applied AI/ML or Generative AI solutions
- Familiarity with MCP, Agent Skills, and architectures connecting models to tools and data through standardized interfaces
- Familiarity with LLM application patterns including embeddings, vector search, prompt orchestration, tool calling, safety, guardrails, and evaluation
- Strong software engineering experience delivering production systems with maintainable architectures and clean, testable code
- Proficiency in Java and/or Python
- Experience building APIs and services and integrating with data sources and downstream systems
- Experience deploying solutions on AWS and cloud-native environments
- Understanding of security fundamentals and operational excellence
- Experience with CI/CD, code reviews, unit testing, and deployment automation
- Experience with containers and orchestration such as Docker and Kubernetes/EKS
- Experience with production monitoring practices
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
-
Healthcare Strength — Medical, dental, vision, and mental-health coverage are broad, with wellness incentives, on-site or virtual care, and an EAP offering coaching and counseling. Plan materials emphasize accessible options, including multiple medical choices and tools to manage costs.
-
Parental & Family Support — Paid parental leave extends up to 16 weeks for all parents, supplemented by paid Critical Caregiver Leave. Family resources include backup childcare via Bright Horizons, lactation support and milk-shipping, family-building assistance, and even a free five-month SNOO rental for newborns.
-
Retirement Support — Retirement programs include a 401(k) with an annual company match and automatic pay credits for most employees, with a legacy pension available to earlier hires. An Employee Stock Purchase Plan at a 5% discount further supports long-term savings.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
Gallery
