Agentic Development Team Leader / Associate

JPMorganChase · India · 5+ yrs experience · Posted 2026-01-16

Tech stack: AWS, Docker, Kubernetes, Python, Terraform

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About the role

The Data, Analytics and Reporting Team (DART) serves as the primary provider of data analytics and automation solutions for all functions within the Consumer and Community Banking Operations. As a global team with a presence in the United States, India, and the Philippines, this role offers the opportunity to develop cutting-edge solutions and infrastructure. The position involves collaboration with various stakeholders and management levels to ensure the delivery of the most effective solutions.
Responsibilities:
- Design, test, and maintain
- modular components for agentic systems to enable intelligent automation and orchestration within business platforms.
- responsibility for individual workstreams and Jira stories, consistently delivering high-quality code and features as part of broader AI/ML initiatives.
- Collaborate
- effectively with team members to integrate agentic capabilities into existing systems and support solution delivery.
- Containerize
- and deploy agentic system components on cloud platforms (preferably AWS), adhering to established DevOps and infrastructure-as-code practices.
- Leverage
- advancements in agentic frameworks (such as LangGraph, Google ADK, AutoGen), LLMs, and GenAI by staying current and applying these technologies to assigned tasks and features.
- Document
- design decisions, implementation details, and results; proactively communicate progress and technical concepts to team members and stakeholders.
- code quality, security, and compliance through rigorous testing, peer reviews, and adherence to best practices.
- Lead a team of senior resources focused on agentic solutions, infrastructure development, CI/CD pipeline, and application development.
- Establish
- strong partnerships with similar teams across locations, as well as with other internal and external stakeholders, to enhance stakeholder management.
Qualifications:
- Bachelor’s degree with years experience or Master’s degree with 5+ year experience in a quantitative field (e.g., Computer Science, Data Science, Applied Mathematics, Statistics, Engineering).
- Hands-on experience developing and delivering agentic system components or autonomous AI features in production environments.
- Strong Python programming skills, with a focus on modular, scalable, and maintainable code.
- Experience with cloud platforms (AWS ), containerization (Docker), and infrastructure as code (Terraform).
- Familiarity with agentic frameworks (LangGraph, Google ADK, AutoGen) and integrating AI capabilities into business processes.
- Ability to work collaboratively in agile, cross-functional teams and deliver on assigned workstreams.
- Excellent problem-solving, communication, and documentation skills.
- Ability to lead self and work independently, keeping all stakeholders informed.
- Experience with Large Language Models (LLMs), GenAI, and retrieval-augmented generation (RAG).
- Exposure to agentic system design patterns, orchestration, and workflow automation.
- Experience with distributed computing, cloud orchestration (Kubernetes, EKS), and MLOps tools.
- Financial services industry experience.
- Ability to design and evaluate autonomous system features aligned with business goals.
- Experience with additional cloud services (EKS, S3, RDS, CloudFormation).

Qualifications

- Bachelor’s degree with years experience or Master’s degree with 5+ year experience in a quantitative field (e.g., Computer Science, Data Science, Applied Mathematics, Statistics, Engineering).
- Hands-on experience developing and delivering agentic system components or autonomous AI features in production environments.
- Strong Python programming skills, with a focus on modular, scalable, and maintainable code.
- Experience with cloud platforms (AWS ), containerization (Docker), and infrastructure as code (Terraform).
- Familiarity with agentic frameworks (LangGraph, Google ADK, AutoGen) and integrating AI capabilities into business processes.
- Ability to work collaboratively in agile, cross-functional teams and deliver on assigned workstreams.
- Excellent problem-solving, communication, and documentation skills.
- Ability to lead self and work independently, keeping all stakeholders informed.
- Experience with Large Language Models (LLMs), GenAI, and retrieval-augmented generation (RAG).
- Exposure to agentic system design patterns, orchestration, and workflow automation.
- Experience with distributed computing, cloud orchestration (Kubernetes, EKS), and MLOps tools.
- Financial services industry experience.
- Ability to design and evaluate autonomous system features aligned with business goals.
- Experience with additional cloud services (EKS, S3, RDS, CloudFormation).

Responsibilities

- Design, test, and maintain modular components for agentic systems to enable intelligent automation and orchestration within business platforms.
- responsibility for individual workstreams and Jira stories, consistently delivering high-quality code and features as part of broader AI/ML initiatives.
- effectively with team members to integrate agentic capabilities into existing systems and support solution delivery.
- Containerize and deploy agentic system components on cloud platforms (preferably AWS), adhering to established DevOps and infrastructure-as-code practices.
- Leverage advancements in agentic frameworks (such as LangGraph, Google ADK, AutoGen), LLMs, and GenAI by staying current and applying these technologies to assigned tasks and features.
- Document design decisions, implementation details, and results; proactively communicate progress and technical concepts to team members and stakeholders.
- code quality, security, and compliance through rigorous testing, peer reviews, and adherence to best practices.
- Lead a team of senior resources focused on agentic solutions, infrastructure development, CI/CD pipeline, and application development.
- Establish strong partnerships with similar teams across locations, as well as with other internal and external stakeholders, to enhance stakeholder management.

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