Lead Machine Learning Engineer - Generative AI and Agent Platforms

慨正橡扯; Jersey City (NJ); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Health insurance

Retirement plan

Tuition reimbursement

Mental health support

Financial coaching

Job summary

JPMorganChase seeks an Applied AI and Machine Learning Lead to design and operate an agent runtime and its AI capabilities across corporate and payments domains. You will own end-to-end agent solutions, combining engineering discipline with rigorous evaluation, safety, and operational excellence.

You will partner with product, engineering, and business stakeholders to deliver auditable AI capabilities at enterprise scale, leveraging platforms like Databricks, cloud services, and advanced

Qualifications

• Formal training or certification on applied AI and machine learning concepts and 5+ years applied experience
• Bachelor's degree in Computer Science, Engineering, Statistics, or a related field, or equivalent practical experience
• Minimum 7 years of software development experience, including at least 4 years delivering artificial intelligence or machine learning solutions
• Hands-on experience building large language model-powered or agentic applications in production, including tracing, evaluations, and safety guardrails
• Strong programming skills in Python, including strong fundamentals in data structures, algorithms, and applied statistics
• Practical experience with retrieval-augmented generation, including embedding strategies, retrieval quality measurement, and use of vector databases
• Proficiency operating production workloads in at least one of the following: Amazon Web Services, Microsoft Azure, or Kubernetes
• Experience designing data models and building systems using both SQL and NoSQL technologies for real-time or near-real-time use cases
• Strong communication skills and the ability to partner effectively with senior technical and business stakeholders

Responsibilities

• Design and deliver production AI agents across a federated portfolio, owning solutions from prototype through launch and operational support
• Engineer retrieval systems that perform reliably in production, including hybrid retrieval-augmented generation patterns (vector search plus graph-based retrieval where appropriate) with robust chunking, ranking, and grounding approaches
• Implement agent memory patterns, including episodic and semantic memory with recall, summarization, and decay policies aligned to use-case needs
• Build entitlement-aware and tenant-aware context assembly so agents reason only over permitted data, supporting traceability and auditability
• Orchestrate multi-agent workflows and integrate external tools and data sources through secure connectors and standardized tool interfaces
• Develop evaluation frameworks, including task-level and end-to-end evaluations, regression suites, automated scoring, and release gates for quality and safety
• Deploy and operate agent services on public cloud platforms (Amazon Web Services and/or Microsoft Azure), applying strong software development lifecycle, security, resiliency, and observability practices
• Optimize runtime performance and reliability by instrumenting tracing, monitoring, and incident-response playbooks for agent services
• Partner with product and business leaders to translate use cases into shipped capabilities, define success metrics, and drive continuous improvement based on production feedback

Skills

LLM development

Python

RAG systems

Vector databases

Kubernetes

AWS/Azure

SQL/NoSQL

Stakeholder communication

Software development

Safety guardrails

Education

Bachelor's degree in Computer Science, Engineering, Statistics, or related field

Tools

Databricks

Kubernetes

Job description

JOB DESCRIPTION

You'll build and ship agents that real businesses depend on, not demos. Platform already runs a federated portfolio of production agents – forecasting, anomaly detection, log analysis, with sales fulfillment and voice‑of‑client close behind – and you'll add to it. You'll work across Corporate & Investment Bank sub‑lines of business and Payments, using Platform's runtime, retrieval, and memory primitives plus platforms such as Databricks and the GenAI Gateway, and apply MLOps for automation, continuous delivery, and compliance with AI/ML control expectations. Platform is the firm's agent runtime: it gives agents secure execution, agent‑to‑agent (A2A) communication, MCP‑based tool access, a managed memory layer, and permission‑aware, auditable operation in a regulated environment. Your job is to turn that platform into shipped agents.

APPLIED AI AND MACHINE LEARNING LEAD

As an Applied AI and Machine Learning Lead at JPMorganChase within Payments Technology, Data Analytics, Regulatory & Compliance (Data Analytics) in the Commercial & Investment Bank, you will build and operate unique Agentic operation system and runtime that allows engineering teams build and safely, reliably run their AI agents. You will also build own AI Agents that solve high‑impact business problems with measurable outcomes. You will own agent solutions end‑to‑end, combining strong engineering discipline with rigorous evaluation, safety, and operational excellence. You will partner with product, engineering, and business stakeholders to deliver reliable, auditable AI capabilities at enterprise scale.

JOB RESPONSIBILITIES

• Design and deliver production AI agents across a federated portfolio, owning solutions from prototype through launch and operational support
• Engineer retrieval systems that perform reliably in production, including hybrid retrieval‑augmented generation patterns (vector search plus graph‑based retrieval where appropriate) with robust chunking, ranking, and grounding approaches
• Implement agent memory patterns, including episodic and semantic memory with recall, summarization, and decay policies aligned to use‑case needs
• Build entitlement‑aware and tenant‑aware context assembly so agents reason only over permitted data, supporting traceability and auditability
• Orchestrate multi‑agent workflows and integrate external tools and data sources through secure connectors and standardized tool interfaces
• Develop evaluation frameworks, including task‑level and end‑to‑end evaluations, regression suites, automated scoring, and release gates for quality and safety
• Deploy and operate agent services on public cloud platforms (Amazon Web Services and/or Microsoft Azure), applying strong software development lifecycle, security, resiliency, and observability practices
• Optimize runtime performance and reliability by instrumenting tracing, monitoring, and incident‑response playbooks for agent services
• Partner with product and business leaders to translate use cases into shipped capabilities, define success metrics, and drive continuous improvement based on production feedback

REQUIRED QUALIFICATIONS, CAPABILITIES AND SKILLS

• Formal training or certification on applied AI and machine learning concepts and 5+ years applied experience
• Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, or a related field, or equivalent practical experience
• Minimum 7 years of software development experience, including at least 4 years delivering artificial intelligence or machine learning solutions
• Hands‑on experience building large language model‑powered or agentic applications in production, including tracing, evaluations, and safety guardrails
• Strong programming skills in Python, including strong fundamentals in data structures, algorithms, and applied statistics
• Practical experience with retrieval‑augmented generation, including embedding strategies, retrieval quality measurement, and use of vector databases
• Proficiency operating production workloads in at least one of the following: Amazon Web Services, Microsoft Azure, or Kubernetes
• Experience designing data models and building systems using both SQL and NoSQL technologies for real‑time or near‑real‑time use cases
• Strong communication skills and the ability to partner effectively with senior technical and business stakeholders

PREFERRED QUALIFICATIONS, CAPABILITIES AND SKILLS

• Experience with agent frameworks and multi‑agent orchestration patterns, including agent‑to‑agent coordination and Model Context Protocol integrations
• Experience with knowledge graphs and graph databases to improve retrieval quality, explainability, and audit readiness
• Understanding of model optimization techniques, including fine‑tuning approaches and efficient inference for smaller models
• Experience developing user‑facing applications using modern JavaScript or TypeScript frameworks for agent user interfaces
• Experience delivering AI solutions in financial services or payments environments with high reliability and control expectations
• Familiarity with Go or Rust for performance‑sensitive services

ABOUT US

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.

BENEFITS

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.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

ABOUT THE TEAM

J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.