Lead Infrastructure Engineer

JPMorgan Chase & Co.•Columbus, OH

About The Position

JPMorgan Chase is seeking a Lead Infrastructure Engineer to provide recommendations and insight on data management, governance procedures, and intricacies applicable to the acquisition, maintenance, validation, and utilization of data. This role involves working with team members, including offshore teams, to resolve high-priority issues, managing GAIA application pools, and designing and maintaining reliable software solutions for monitoring and alerting. The engineer will also address database performance issues, support PostgreSQL and vector database platforms for AI/ML workloads, and utilize AI tools to enhance productivity and speed up issue resolution. Collaboration with globally distributed teams is essential to ensure consistent coverage and knowledge sharing. The position includes supporting an on-call rotation and contributing to a team culture of diversity, equity, inclusion, and respect.

Requirements

7+ years of hands-on experience managing enterprise databases and supporting infrastructure in large-scale, mission-critical environments.
Deep hands-on experience with relational databases, particularly Microsoft SQL Server, plus working experience with PostgreSQL.
Proficiency with Transact-SQL (T-SQL).
Experience designing, deploying, and troubleshooting SQL infrastructure, including Availability Groups (replication and failover).
Working knowledge of vector databases (e.g., pgvector, Pinecone, Milvus, Chroma) and how they support AI/LLM retrieval and search workloads.
Experience with PowerShell scripting and ETL processes.
Experience with database performance troubleshooting and tuning, including tools such as SQL Sentry.
Experience designing and maintaining monitoring and alerting solutions at scale.
Ability to work collaboratively with cross-functional teams, including non-technical business stakeholders and offshore teams.
Experience with internal cloud applications.
Strong communication skills, with the ability to convey complex technical concepts to non-technical audiences.
Experience with version control systems like Git and Bitbucket for data.
A track record of applying AI tools to automate database operations, modernize workflows, and resolve issues more efficiently.
A forward-looking mindset toward AI-driven transformation, with a demonstrated interest in modernizing database automation and tooling using AI capabilities.

Nice To Haves

Experience with SQL Server Availability Groups.
Proficiency with PowerShell.
Solid understanding of Transact-SQL.
Experience with internal cloud application infrastructure.
Experience with overall SQL troubleshooting.
Experience working with offshore or globally distributed engineering teams.
Experience with PostgreSQL administration and performance tuning.
Experience with vector database platforms and retrieval-augmented generation (RAG) architectures.
Experience with developing AI agents, Skills, MCPs, and custom targeted agent profiles.
Hands-on experience using AI coding assistants (GitHub Copilot and/or Claude) and applying them to database automation, scripting, and operational tooling.

Responsibilities

Provides recommendations and insight on data management, governance procedures, and intricacies applicable to the acquisition, maintenance, validation, and utilization of data.
Works with other team members, including offshore teams, to resolve high-priority issues.
Helps manage GAIA application pools.
Designs and maintains reliable software solutions for monitoring and alerting as needed.
Works with the team on database performance issues, including code and infrastructure issues, sometimes using SQL Sentry.
Monitors and troubleshoots SQL Server Availability Groups, including replication issues, database failovers, and general troubleshooting.
Works with the team on certificate tracking and renewals.
Supports PostgreSQL environments and vector database platforms used for AI/ML retrieval workloads, including embedding storage, indexing, and query performance.
Uses AI tools and agents in day-to-day work to increase productivity, automate routine tasks, and speed up issue diagnosis and resolution.
Partners with offshore and globally distributed teams to ensure consistent coverage, knowledge sharing, and delivery across time zones.
Supports the on-call rotation for the team.
Adds to a team culture of diversity, equity, inclusion, and respect.