Principal AI & Data Engineer — FinTech Scale & Security

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase & Co. in Jersey City seeks a Principal Software Engineer to deliver trusted market-leading technology in a secure, scalable way within the Corporate Sector.

You will lead design and implementation of AI-enabled engineering workflows, mentor engineers, and collaborate with senior stakeholders to shape technical strategy across data, AI, and platform domains. The role requires deep expertise in Python/Java, cloud-native platforms, and large-scale data processing, with a focus on

Qualifications

• Formal training or certification in software engineering with 7+ years of applied experience.
• Experience delivering system design, application development, testing, and operational stability at enterprise scale.
• 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; Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field.
• Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data.
• Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.

Responsibilities

• Architects and implements complex, scalable engineering frameworks and solutions using modern software design principles
• Develops secure, high-quality production code for data-intensive applications and platforms, and reviews and mentors other engineers
• Creates durable, reusable software frameworks and patterns that are leveraged across teams and functions
• Designs and governs agentic AI systems, including multi-agent workflows, tool-use integrations, and human-in-the-loop controls appropriate for regulated financial services environments
• Establishes engineering standards for LLM-based applications — RAG pipelines, embedding workflows, vector store integrations, and model serving — ensuring safety, observability, and reproducibility at scale
• Drives adoption of advanced technical methods and practices aligned with the latest industry standards and product development methodologies
• Serves as the function's go-to subject matter expert in one or more areas of focus within data engineering, platform architecture, or AI systems
• Advises cross-functional teams on technological matters within your domain of expertise
• Influences leaders and senior stakeholders across business, product, and technology teams on technical strategy and direction
• Architects and governs agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation at scale.

Skills

Python

Java

LLM systems

Architectural leadership

Microservices

Tools

Kafka

Redis

Dynatrace

Splunk

Grafana

Airflow

Temporal

Databricks

Snowflake

Spark / PySpark

Apache Iceberg

Job description

JPMorgan Chase & Co. in Jersey City seeks a Principal Software Engineer to deliver trusted market-leading technology in a secure, scalable way within the Corporate Sector.

You will lead design and implementation of AI-enabled engineering workflows, mentor engineers, and collaborate with senior stakeholders to shape technical strategy across data, AI, and platform domains. The role requires deep expertise in Python/Java, cloud-native platforms, and large-scale data processing, with a focus on