Live opening · Posted 7 days ago
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Join a team where your advanced engineering skills drive impactful solutions for a global financial leader. Grow your career while shaping the future of data-driven risk assessment.
Job summary
As a Senior Lead Software Engineer at JPMorgan Chase within the Corporate Sector Data Engineering team, you will deliver secure and scalable solutions that support the firm’s Global Know Your Customer (KYC) and Risk Assessment Data Platform. You will collaborate with talented colleagues to drive best-in-class outcomes and set engineering standards. Your leadership will help define architecture and practices across multiple teams. Together, we create trusted platforms that power the firm’s critical risk management initiatives.
Job responsibilities
Develop secure, high-quality production code for data-intensive applications and platforms, and mentor other engineers
Create durable, reusable software frameworks and patterns leveraged across teams and functions
Design and govern agentic AI systems, including multi-agent workflows, tool-use integrations, and human-in-the-loop controls for regulated environments
Establish engineering standards for LLM-based applications, ensuring safety, observability, and reproducibility at scale
Drive adoption of advanced technical methods and practices aligned with industry standards and product development methodologies
Advise cross-functional teams on technological matters within your domain of expertise
Apply knowledge of tools within the Software Development Life Cycle toolchain, including AI-assisted development and automation capabilities, to improve automation at scale
Required qualifications, capabilities and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
Hands-on practical experience delivering system design, application development, testing, and operational stability at enterprise scale
Hands-on experience designing and deploying production AI/ML systems, including LLM-based applications and agentic architectures with tool use, memory, and multi-step reasoning in regulated environments
Expert in one or more programming languages, particularly Python and/or Java
Advanced knowledge of software application development and technical processes, with considerable depth in one or more disciplines (e.g., cloud, AI/ML, data engineering)
Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal)
Advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance
Practical cloud-native experience (AWS, Azure, or GCP)
Ability to present and effectively communicate with senior leaders and executives
Preferred qualifications, capabilities and skills
Experience with modern data platforms such as Databricks or Snowflake
Deep hands-on experience with Spark/PySpark and other big data processing technologies
Expertise in open-source table formats and catalog services such as Apache Iceberg
Experience with LLM orchestration frameworks and model serving infrastructure or managed endpoints (AWS Bedrock, Azure OpenAI)
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