Lead Software Engineer - Databricks/PySpark/AI

JPMorgan Chase & Co.
Wilmington, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Wilmington, United States of America

Tech stack

API
Agile Methodologies
Artificial Intelligence
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Automated Storage and Retrieval Systems
Big Data
Code Review
Encodings
Computer Programming
Continuous Integration
Data as a Services
Information Engineering
Data Infrastructure
Data Retrieval
Data Warehousing
Software Debugging
DevOps
Python
Query Optimization
Standard Sql
DataOps
Search Technologies
Software Engineering
Unstructured Data
Enterprise Data Management
Large Language Models
Snowflake
Spark
Generative AI
Data Lake
PySpark
Production Code
Amazon Web Services (AWS)
Data Management
Virtual Agents
Api Design
Amazon Web Services (AWS)
Terraform
Data Pipelines
Databricks

Job description

As a Lead Software Engineer - Databricks/PySpark/AI at JPMorganChase within the Corporate Sector-Global Finance team, you will serve as a senior hands-on developer and technical leader within an agile team, responsible for building, delivering, and optimizing cutting-edge data products that power agentic AI systems - autonomous AI agents capable of planning, reasoning, and executing multi-step tasks. In this role, you will write production-quality code daily, drive implementation of essential technology solutions including data infrastructure, tool integrations, and retrieval systems that enable AI agents to access, interpret, and act on enterprise data in support of the firm's business goals. You will be expected to mentor junior engineers, collaborate with cross-functional stakeholders, and champion engineering excellence through hands-on delivery.

Job Responsibilitie

  • Building and optimizing data pipelines and workflows that serve as the backbone for agentic AI systems, ensuring agents have reliable, real-time access to high-quality, structured and unstructured data

  • Developing data retrieval and indexing layers that enable AI agents to autonomously search, query, and synthesize information across multiple data sources

  • Building and maintaining tool-use infrastructure - APIs, data services, and function endpoints - that AI agents invoke to execute tasks, retrieve data, and interact with enterprise systems

  • Implementing and enforcing best practices for data management, ensuring data quality, security, and compliance, including governance of data consumed and generated by autonomous AI agents

  • Hands-on development of secure, high-quality production code following AWS best practices, and deploying efficiently using CI/CD pipelines; Building orchestration and state management layers that support multi-step agent workflows, including memory, context persistence, and task chaining

  • Writing and reviewing code daily, conducting thorough code reviews, and raising the technical bar across the team; Mentoring and guiding junior and mid-level engineers through pairing, code reviews, and technical coaching

  • Collaborating with product owners, data scientists, and business stakeholders to translate business requirements into working, production-ready agentic AI solutions; Evaluating and adopting emerging agentic AI frameworks, tools, and data engineering practices to continuously improve the team's development capabilities

Requirements

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Expert-level programming skills in Python/PySpark with a strong portfolio of production-grade code
  • Extensive hands-on experience with Databricks and the AWS cloud ecosystem, including AWS Glue, S3, SQS/SNS, Lambda
  • Deep expertise with Spark and SQL
  • Strong hands-on experience with Lakehouse/Delta Lake architecture, application development, testing, and ensuring operational stability; Snowflake, Terraform and LLMs; Data Observability, Data Quality, Query Optimization & Cost Optimization
  • In-depth knowledge of Big Data and data warehousing concepts at enterprise scale
  • Extensive experience with CI/CD processes and automated testing frameworks
  • Solid understanding of agile methodologies, including DevOps practices, application resiliency, and security measures
  • Understanding of agentic AI concepts - how autonomous AI agents plan, reason, use tools, and execute multi-step workflows - and the data infrastructure required to support them
  • Experience building APIs, data services, and retrieval systems that serve as the connective tissue between AI agents and enterprise data
  • Demonstrated ability to lead by example through code, mentor engineers, and drive delivery across the team, * Experience with agentic AI frameworks (e.g., LangGraph, AutoGen, CrewAI, OpenAI Assistants API) and understanding of how data engineering underpins agent orchestration
  • Familiarity with tool-use and function-calling patterns for LLM-based agents, including building and exposing APIs and data endpoints that agents can invoke autonomously
  • Experience with vector databases (e.g., Pinecone, FAISS, Chroma) and embedding workflows for powering agent memory, semantic search, and retrieval-augmented generation (RAG)
  • Exposure to agent memory and state management patterns - short-term context windows, long-term persistent memory stores, and conversation/task history management
  • Familiarity with guardrails and safety frameworks for autonomous AI systems, including input/output validation, action approval workflows, and human-in-the-loop controls
  • Understanding of observability and monitoring for agentic systems - tracing agent decision paths, logging tool invocations, and debugging multi-step autonomous workflows
  • Understanding of responsible AI principles, particularly around autonomous decision-making, data provenance, and auditability of agent actions

Benefits & conditions

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.

About the company

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., 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.

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