Principal Software Engineer - AI Engineer

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 as needed) 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 (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes 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.
• 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, working across product, risk, legal, and compliance teams.
• 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.

About The Role

As a Principal Software Engineer at JPMorganChase within the Corporate Sector - AI/ML & Data Platforms for LLM Suite, you will lead a specialized technical area, driving impact across teams, technologies, and projects. You will leverage your deep knowledge of machine learning, software engineering, and product management to spearhead multiple complex ML projects and initiatives, serving as the primary decision-maker and a catalyst for innovation and solution delivery.

Job Title

Principal Software Engineer - AI/ML & Data Platforms for LLM Suite