Lead Software Engineer & ML Engineer - Sales Copilot

Salary: $61,000 - 101,000 per year Requirements:

• Formal software engineering training or certification, plus at least 5 years of applied experience, including 4 or more years working on AI/ML solutions.
• Practical experience across system design, application development, testing, and operational stability.
• Strong Python programming skills and advanced ability in one or more programming languages; knowledge of data structures, algorithms, machine learning, data mining, information retrieval, and statistics.
• Experience delivering production LLM-powered or agentic applications, including tracing, evaluation, and guardrails.
• Expertise in Kubernetes and Amazon EKS, micro-VM isolation technologies such as Firecracker, Kata Containers, or gVisor, and sidecar architectures. Demonstrated ability to apply defense in depth across networking and mTLS, workload identity, fine-grained authorization, runtime isolation, and application-level guardrails.
• Practical RAG experience, including retrieval quality, embeddings, and vector stores; expert knowledge of at least one of AWS, Azure, or Kubernetes.
• Knowledge of data management and data model design, and real-time processing with SQL databases such as Postgres and NoSQL stores such as OpenSearch or Redis.
• Strong communication skills and the ability to work effectively with senior technical and business stakeholders.
• Proficiency across the software development life cycle.
• Advanced understanding of agile practices, CI/CD, application resiliency, and security.
• In-depth knowledge of financial services and its IT systems.
• Preferred: A masters degree in computer science, statistics, mathematics, machine learning, or a related discipline, or equivalent experience.
• Preferred: Experience with agent frameworks or runtimes, A2A, MCP, agent memory design, or organizational context management.
• Preferred: Knowledge of knowledge graphs and graph databases for retrieval; Graph RAG experience is a strong advantage.
• Preferred: Understanding of LLM fine-tuning and small language model inference.
• Preferred: Ability to build full-stack products using modern JavaScript or TypeScript frameworks, such as Next.js or Svelte, for agent user interfaces.
• Preferred: Experience in financial services or payments at a large institution, such as investment banking, markets, or securities services.
• Preferred: Knowledge of high-performance languages such as Go or Rust.

• Design, build, and deliver production agents on NEO across our federated portfolio, taking solutions from prototype through production.
• Develop production-ready retrieval, including Graph RAG, knowledge-graph traversal, vector search, chunking, ranking, and grounding approaches that support accurate, auditable answers.
• Design agent memory using episodic and semantic memory nodes, with recall, summarization, and decay policies tailored to each use case.
• Manage organizational context by assembling entitlement-, lineage-, and tenant-aware information so agents only use data they are permitted to access.
• Create multi-agent workflows using A2A and connect tools and data through MCP servers, including Bitbucket, Confluence, Databricks, Kubernetes, Snowflake, and Splunk.
• Build task-level and end-to-end evaluations, regression suites, LLM-as-judge processes, and quality and safety checks before release.
• Deploy and operate solutions on public cloud platforms such as AWS or Azure, applying strong SDLC, security, resiliency, and observability practices.
• Work with product and business partners across the Commercial & Investment Bank and Payments to turn use cases into deployed, supported agents.
• Lead evaluation sessions with external vendors, startups, and internal teams, assessing architecture, technical capabilities, and fit with existing systems and information architecture.

• AI
• AI Agents
• AWS
• OpenSearch
• Azure
• BitBucket
• CI/CD
• Cloud
• Confluence
• Databricks
• Fine-tuning
• Support
• JavaScript
• Kubernetes
• LLM
• Machine Learning
• MCP
• NoSQL
• Python
• RAG
• Redis
• Rust
• SQL
• Security
• Snowflake
• Splunk
• Svelte
• TypeScript
• DevOps
• Network
• PaaS
• UX UI Design

More:

We are partnering with hackajob to connect professionals with this opportunity at J.P. Morgan. As a Senior AI Application Engineer within our Commercial & Investment Bank Technology organization, Digital & Platform Services, and Data Analytics group, you will help build production AI agents on NEO, our agent runtime platform on AWS and Azure. Our teams collaborate across business, product, and engineering in a fast-paced environment, using our scale, data, and services to deliver impact across the Commercial & Investment Bank and Payments. J.P. Morgan is a global financial institution with a history spanning more than 200 years, serving consumers, businesses, corporations, institutions, and governments. Our Commercial & Investment Bank operates across banking, markets, securities services, and payments, serving clients in more than 100 countries. We offer a competitive total rewards package, with compensation based on role, experience, skills, and location; eligible employees may also receive incentive compensation. Benefits, subject to eligibility, include health coverage, wellness centers, retirement savings, backup childcare, tuition reimbursement, mental health support, and financial coaching. We value diversity and inclusion and provide reasonable accommodations for religious practices, beliefs, and disability-related needs.

last updated 41 week of 2026