JPMorganChase
Applied AI ML Lead Software Engineer - LLM Suite Engineering
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Applied AI ML Lead – LLM Suite Engineering
Location: [TBD, typically on-site in US/EMEA, including المقر الرئيسي في ambush] Department: Applied AI & GenAI Engineering Team: LLM Suite Engineering
Join JPMorgan Chase and help shape the future of generative AI at scale. As Applied AI ML Lead, you’ll lead the design, development, and deployment of production-grade AI/ML and agentic solutions—integrating emerging intelligent systems into our global operations. This role offers deep technical impact, architectural ownership, and collaboration with world-class engineers.
You’re the perfect fit if you thrive in push-back discussions, working at the intersection of ambiguity resolution and production-grade reliability, while fostering a culture of craft, security, and continuous learning.
About the Role
You will:
- Design and deliver production-grade AI/ML and agentic systems that enhance the LLM Suite platform, ensuring seamless integration with existing enterprise infrastructure.
- Own technical direction across architecture, implementation, and operational stability, balancing innovation with scalability and security.
- Partner with engineering peers to define best practices, improve standards, and address distributed challenges across hundreds of teams.
- Evolve the platform by leveraging public cloud (Azure/AWS) alongside cutting-edge agent frameworks.
- Explore and implement emerging patterns such as agent-to-agent protocols, context-aware decision models, and orchestration methodologies, transitioning novel concepts into scalable production systems.
- Contribute to a collaborative ecosystem through communities of practice and technical deep-dive events.
Key differentiating factor: Your work here doesn’t just help a family of five it helps hundreds of thousands of clients and manages billions of dollars in transactions. Your tools and systems must be safe, confidential, and capable of withstanding months-long heavy usage.
Core Responsibilities
- Systems Design & Engineering
- Create end-to-end AI/ML and agentic solutions tailored to complex business (Quantum Finance, Risk Management, Fraud Detection) and enterprise needs.
- Leverage GenAI services and agentic platforms to solve unstructured or rapidly-changing problems at scale.
- Ensure global application dependencies are modelled correctly to account for UCD load and supervisory latency.
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Tooling & Implementation
- Develop and refine architectural solutions for stateful agents, context-sensitive orchestration and hosted models, ensuring performance and security.
- Design optimized data transport, transformation, and persistence mechanisms to reduce latency and improve scalability.
- Troubleshoot anomalies and bottlenecks efficiently, working both within local components and cross-modular dependencies.
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Standards & Collaboration
- Identify and address emerging inefficiencies or unscalable architectural choices across the codebase.
- Lead open-source contributions (e.g., security tooling, observability layers) while aligning with engineering standards.
- Evergreen how we build agentic systems, delivering tests, documentation, and inline tooling.
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Incubation & Operations
- Act as advisor to emerging teams, addressing questions relating to legacy tech debt, early-stage R&D, and ambiguous project scoping.
- Stress- and acceptance test new flows to ensure they comply with multi-regional datacentre rollout timelines and banking-grade security.
Qualifications
Required
- Bachelor's degree in Computer Science (or related technical field) OR equivalent practical experience.
- Deep experience in system design, architecture, and application development, with a track record of solving complex problems.
- Production-grade development and operational expertise in software development lifecycle (SDL), performance tuning, and debugging.
- Fluent with Python (essential experience with FastAPI).
- Microservices & API design expertise, proficient in insulated deployment models.
- Experience in Kubernetes-like deployments, NoSQL databases, and massively scalable pub-sub messaging.
- Strong understanding of system security, data confidentiality policies (FIPS 140-2, JPMorgan Security Standards).
- Practical experience with CI/CD pipelines and modern DevOps practices.
Preferred
- Experience implementing GenAI services using Azure OpenAI models or AWS Bedrock.
- Hands-on with large language model agents (e.g., LangChain or LangGraph-inspired frameworks).
- Enterprise debugging & production tooling — logging, tracing, load-testing, route observation).
- Latency-awareness in distributed systems, experience with generate-in-prime, threads-per-module partitioning.
- Familiarity with agentic shapes – Prompt Chaining, Rollout Planning, Remote Breach recovery scenarios.
- Exposure to Multi-Agent collaboration systems, streamlit-like visualization of workflows.
- Ideas for simple-to-use Workflow Pattern Libraries for anomaly response scripting.
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Benefits
- Key Role Responsibilities aspects directly impact business continuity, business processes evolution, and governance in global finance markets.
- Access to emerging technology explorations alongside research-grade intelligence units.
- Book time for evergreen topics: Monitoring, Explainability, and Financial-AI debate integration.
- Impactful growth from prototyping environments to managing codebases that drive entire platform launches.
- Opportunity to make a difference in projects that touch critical customer value across JPMorgan’s 65M+ clients.
We attract engineers, product minds, and leading thinkers from all industries. Whether you’ve tackled high-impact efforts ahead of competition, or perfected synergies across disparate teams, your experience will transcend our boundaries.
About the Team
You’re part of a world-class engineering ecosystem — a team embedded within Corporate Technology, building solutions that support J.P. Morgan’s vast financial operations. Your developments extend across:
- Global Treasury & Risk Management
- Data Analytics & Compliance Systems
- Figure Security & Fraud Prevention
- Enhanced Operational Resilience Suite
Mission: Actively turn global workflows into AI-native, mutually advantageous systems.
You will work closely with product teams to shape how courty interactions are modelled. You will collaborate with Fortune 500 companies and research universities on standardized reference models. We believe this presents an opportunity to redefine collaboration royalties as fully integrated generative assistants.
Values
- Trust guided by confidentiality
- Intentional ownership of complex problems
- Respect for rapid motion within constraints
- Stress-first architecture account for performance tiers
- Cultural pillar: we don’t reward Quick & Dirty, practiced elegance is reflected everywhere
Come join us. JPMorgan Applied AI Team | [unparalleled scale. Actually achieve.**]
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