Principal Software Engineer - AI Engineer

JPMorganChase; Jersey City (NJ); On-site; USD 130,000 - 160,000; Full time

Job summary

Join JPMorganChase as a Principal Software Engineer focusing on AI/ML and Data Platforms. You will lead technical areas and drive innovations across teams.

The ideal candidate has extensive experience in software engineering, specifically in developing LLM-backed services. Responsibilities include designing AI architectures and optimizing ML lifecycles.

This position offers a chance to make significant impacts across various projects using cutting-edge technology.

Qualifications

• 7+ years of applied experience in software engineering.
• Proven experience deploying LLM-backed services to production.
• Ability to influence senior technical leaders effectively.

Responsibilities

• Lead the design and implementation of AI reference architectures.
• Build and operate LLM-powered APIs and microservices.
• Optimize machine learning lifecycle for efficiency.

Skills

Python engineering skills

Experience with PyTorch or TensorFlow

Expertise with vector storage systems

Expertise developing long-running agents

Deep MLOps experience

Cloud-native AI deployment (AWS or Azure)

Strong communication skills

Experience with prompt engineering

Education

Formal training or certification in software engineering

Job description

Job Description

Principal Software Engineer – AI/ML & Data Platforms for LLM Suite at JPMorganChase. Lead a specialized technical area, drive impact across teams, technologies, and projects, and spearhead complex ML initiatives. Serve as primary decision‑maker and catalyst for innovation and solution delivery for JPMorganChase’s premier internally built AI tool used by over 250k employees.

Job Responsibilities

• Design and implement agentic AI reference architectures, including orchestration, retrieval, memory, guardrails, and evaluation harnesses.
• Write production‑quality Python code (PyTorch or TensorFlow) and review critical‑path code.
• Create reusable components for prompt management, evaluators, safety filters, connectors, embeddings pipelines, and memory stores.
• Build and operate LLM‑powered APIs and microservices integrated into advisor, client, and internal workflows.
• Own the end‑to‑end ML lifecycle: experimentation, CI/CD, automated testing, monitoring, drift detection, versioning, and rollback.
• Optimize inference for latency, throughput, caching, batching, model selection, and cost per inference.
• Partner with data teams on structured and unstructured data pipelines, document ingestion, metadata, and access controls.
• Set engineering standards for agentic AI systems and lead design reviews.
• Influence roadmap and priorities through technical insight and delivery.
• Architect and govern agentic AI‑enabled engineering workflows to improve delivery speed, code quality, and operational outcomes at scale, defining guardrails for validation, security, resiliency, and reuse across teams.
• Apply knowledge of tools within the Software Development Life Cycle toolchain to improve automation value at scale.

Required Qualifications, Capabilities, And Skills

• Formal training or certification on software engineering concepts and 7+ years applied experience.
• Strong Python engineering skills; experience with PyTorch or TensorFlow.
• Expertise working with vector storage systems and designing memory for agents.
• Expertise developing long‑running agents that run autonomously with tools, skills, and human in the loop.
• Proven experience deploying LLM‑backed services to production (APIs, microservices).
• Deep MLOps experience, including CI/CD, monitoring, incident response, and model governance.
• Cloud‑native AI deployment experience (AWS or Azure) with cost and performance optimization.
• Demonstrated commitment to responsible AI practices and operational excellence.
• Strong communication and collaboration skills across product, risk, legal, and compliance teams.
• Experience designing and leading adoption of agentic AI‑enabled development practices across teams, setting standards for human‑in‑the‑loop validation, auditability, and secure handling of sensitive data.
• Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications and risk‑based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.

Preferred Qualifications, Capabilities, And Skills

• Experience with fine‑tuning, adapters, or custom evaluation frameworks.
• Background operating AI systems in regulated environments (finance, healthcare, etc.).
• Experience with prompt engineering and LLM orchestration.
• Knowledge of safety filters, audit logging, and explainability in production systems.
• Experience mentoring senior engineers and leading architecture discussions.
• Demonstrated ability to influence technical roadmaps and priorities.

Federal Deposit Insurance Act

This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase's review of criminal conviction history, including pretrial diversions or program entries.

Equal Opportunity Employer

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.