Senior AI Engineer: Python, LLMs & Agentic Workflows

Aumni; Jersey City (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorganChase is seeking a Lead AI Engineer to enhance product offerings by delivering AI-driven features, building production-grade AI applications, and architecting scalable AI systems with strong governance and security controls.

You will drive AI standards, perform architecture reviews, and collaborate with product, risk, and engineering teams to ensure measurable success across the organization.

Qualifications

• Formal training or certification in software engineering concepts and 5+ years of applied engineering experience
• Hands-on experience delivering AI-powered features in production or near-production environments (LLMs, RAG, agents, workflow automation, or decision support systems)
• Strong proficiency in Python (and ability to build maintainable services, libraries, and pipelines)
• Experience building APIs and services using Django, FastAPI, or similar frameworks
• Experience building modern UIs using React or similar frameworks (or strong ability to partner closely with frontend teams)
• Strong system design skills with an emphasis on secure distributed systems, reliability, and operational excellence
• Practical understanding of Responsible AI / model risk concepts (evaluation, guardrails, privacy, bias, explainability where applicable, and safe deployment practices)
• Experience implementing observability (logging, metrics, tracing) and AI-specific monitoring (quality, drift signals, latency, cost, error rates)
• Experience with cloud platforms (AWS preferred) and containerized deployments
• Strong problem-solving skills with a structured, evidence-based approach; comfortable operating in ambiguity and delivering iteratively

Responsibilities

• Enhance multiple products across the product line by identifying, prioritizing, and delivering AI-driven features that improve user experience, efficiency, and operational resilience
• Design, build, and deploy production-grade AI applications including LLM-powered workflows, Retrieval-Augmented Generation (RAG) solutions, and agentic systems
• Build agentic workflows with enterprise-ready controls (identity, authorization, guardrails, tracing, evaluation, and auditability)
• Develop automation solutions that reduce manual effort and eliminate recurring operational issues, including self-healing patterns and intelligent triage
• Architect AI systems with production concerns in mind: latency, scalability, cost management, model selection, observability, reliability, and failure modes
• Establish and apply AI engineering standards across the product line (prompting patterns, RAG design standards, evaluation practices, logging/telemetry, and release readiness criteria)
• Drive AI architecture reviews and contribute to reference architectures for model hosting, orchestration, data access, and secure tool execution
• Identify and mitigate risks across the AI lifecycle including data privacy, security, bias, model misuse, prompt injection, and third-party/vendor risk
• Partner with product, design, risk, legal/compliance, and engineering stakeholders to align on outcomes, constraints, and measurable success metrics
• Lead technical evaluations with vendors and platform providers; assess capabilities, integration fit, security posture, and total cost of ownership
• Research emerging AI capabilities (models, frameworks, tools) and translate findings into practical guidance, prototypes, and adoption recommendations
• Educate and enable teams through documentation, workshops, design reviews, and coaching to raise AI fluency and delivery consistency across the organization
• Execute creative software solutions, technical troubleshooting, and hands-on development; write secure, high-quality production code and review/debug code written by others
• Influence stakeholders and drive alignment across teams without direct authority, owning outcomes end-to-end

Skills

AI feature delivery

Python

Django/FastAPI

React

Secure distributed systems

Responsible AI / model risk

Observability

AWS

Tools

LangChain

LlamaIndex

Semantic Kernel

CrewAI

pgvector

Pinecone

Weaviate

OpenSearch/Elastic

Terraform

Databricks

Job description

JPMorganChase is seeking a Lead AI Engineer to enhance product offerings by delivering AI-driven features, building production-grade AI applications, and architecting scalable AI systems with strong governance and security controls.

You will drive AI standards, perform architecture reviews, and collaborate with product, risk, and engineering teams to ensure measurable success across the organization.