Lead Software Engineer - Data & Applied AI

Salary: $61,000 - 101,000 per year Requirements:

• We require formal training or certification in Software Engineering, along with 5+ years of applied experience.
• We look for demonstrated experience leading the effective use of approved AI-assisted software development tools for coding, code review, test acceleration, and troubleshooting, with clear standards for validating outputs for correctness, performance, and security.
• We need a strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations, plus experience coaching engineers on safe, compliant adoption.
• We need strong knowledge of data architecture and modeling patterns, including dimensional modeling and database design such as normalization and denormalization.
• We expect experience using enterprise-authorized AI-assisted development tools for coding, testing, troubleshooting, and documentation, with rigorous validation of outputs.
• We need the ability to apply and coach responsible AI practices, including secure input and output handling, data sensitivity, and resiliency and security standards.
• We look for experience owning end-to-end delivery of data management products across UI, APIs, services, integrations, and data pipelines in a federated model.
• We need the ability to design and deliver platform services for metadata, lineage, data contracts, data quality, and retention and destruction through well-defined interfaces and workflows.
• We value experience evaluating open-source solutions through rapid proofs of concept, then leading selection, customization, and enterprise hardening for reliability, security, and operational support.
• We need experience building workflow orchestration and policy enforcement services, plus scalable batch and streaming integrations with schema evolution, backfills, error handling, and contract-driven interoperability.
• We expect experience establishing production-grade operations and controls, including SRE practices, monitoring and on-call, incident response and root-cause analysis, auditability, least-privilege, disciplined change management, and governed agentic capabilities.
• We require the ability to lead through influence, design reviews, and mentoring.
• Preferred experience includes financial services or Wealth Management, data governance or data management domain expertise, and evaluating and enterprise-hardening open-source software.
• Preferred technical skills include frontend experience with React or Angular and TypeScript, backend experience with Python, Java, or Kotlin and REST or GraphQL, and data engineering/platform experience with Spark, Kafka, Airflow, Snowflake, and AWS.
• Preferred platform engineering experience includes containers, CI/CD, observability, and controlled release practices.
• Preferred applied AI experience includes LLMs, Claude Code, agents, skills, RAG, embeddings, prompt or configuration management, evaluation and guardrails, and agent tool or function calling.
• A bachelors degree is required, and an advanced degree is a plus.

• We design, develop, and deliver AI-enabled platform capabilities that power next-generation data management products, including data quality, metadata management, lineage, and data retention and destruction.
• We drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational results.
• We use AI-assisted development and automation capabilities within the SDLC toolchain to increase the value we realize from automation.
• We perform hands-on design and development of an agentic production data platform with full-stack application ownership.
• We take an AI-first approach to coding, using Claude Code and building agents that make our application and platform more autonomous.
• We develop AI skills, agents, and MCP servers to support product capabilities and deliver business value.
• We deliver creative software solutions, technical design, development, and troubleshooting beyond routine approaches.
• We leverage AI coding assist tools to improve code quality, delivery speed, and productivity across complex work, while validating outputs through peer review, automated testing, and secure coding standards.
• We develop secure, high-quality production code and review and debug code written by others.
• We identify opportunities to remove recurring issues or automate remediation to improve overall operational stability of software applications and systems.

• AI
• Airflow
• AWS
• Angular
• Backend
• CI/CD
• Claude Code
• Cloud
• Frontend
• GraphQL
• Support
• Java
• Kafka
• Kotlin
• MCP
• Python
• RAG
• REST
• React
• Security
• Snowflake
• Spark
• TypeScript
• UX UI Design
• Network

More:

hackajob is partnering with J.P. Morgan to connect exceptional professionals with this role. We are looking for a Data Engineering & Applied AI Lead Software Engineer within Asset & Wealth Management, where we build trusted, market-leading technology products in an agile, secure, stable, and scalable environment. JPMorganChase is one of the oldest financial institutions, serving consumers, small businesses, and major corporate, institutional, and government clients across the J.P. Morgan and Chase brands, with a history spanning more than 200 years. We offer a competitive total rewards package, with base salary based on role, experience, skill set, and location, and eligible roles may also include commission or discretionary incentive compensation. Our benefits can include comprehensive health care, on-site wellness centers, retirement savings, backup childcare, tuition reimbursement, mental health support, financial coaching, and more. We value diversity and inclusion, provide reasonable accommodations where needed, and operate as an equal opportunity employer, including disability and veterans. Our Asset & Wealth Management team delivers investment management and private banking solutions, and our agile technologists work in a cloud-native, data-centric environment focused on innovation, continuous learning, and helping our clients stay properly invested.

last updated 36 week of 2026