{"id":2224207,"url":"https://alion.io/job/jpmorganchase-lead-machine-learning-engineer-agentic-pricing","title":"Lead Machine Learning Engineer - Agentic Pricing","company":{"id":257,"name":"JPMorganChase","domain":"jpmorganchase.com","url":"https://alion.io/company/jpmorganchase","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":100,"open_postings":483,"ghost_share":0.01,"stale_share":0.112,"repost_share":0.126,"time_to_fill_p50_days":10,"computed_at":"2026-10-13T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Jersey City, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":184000,"max_usd":378000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":640},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A2A","optional":false},{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Bitbucket","optional":false},{"name":"CI/CD","optional":false},{"name":"Confluence","optional":false},{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenSearch","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Redis","optional":false},{"name":"Snowflake","optional":false},{"name":"Splunk","optional":false},{"name":"SQL","optional":false},{"name":"Fine-tuning","optional":true},{"name":"GraphRAG","optional":true},{"name":"JavaScript","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"Next.js","optional":true},{"name":"React.js","optional":true},{"name":"Rust","optional":true},{"name":"Svelte","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2026-10-08T17:37:06Z","employer_posted_date":"2026-10-08","last_verified_at":"2026-10-13T22:10:49Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"Job Summary\nJPMorganChase is hiring top talent to join the growing Corporate & Investment Bank Technology organization within Digital & Platform Services / Data Analytics, building production AI agents on NEO that leverage the firm’s scale, data, and full-service advantage to deliver measurable impact across the Commercial & Investment Bank and Payments.\nAs a Senior AI Application Engineer within the firm’s NEO agent runtime platform on AWS and Azure, you will design, productionize, and operate large language model (LLM)-powered agents, partnering closely with business, product, and engineering teams in a fast-paced environment.\nCore Selling Aspects (Why this role)\nYou’ll build and ship agents that real businesses depend on, not demos. NEO already runs a federated portfolio of production agents - forecasting, anomaly detection, log analysis, with sales fulfillment and voice-of-client close behind - and you’ll add to it.\nYou’ll work across Corporate & Investment Bank sub-lines of business and Payments, using NEO’s runtime, retrieval, and memory primitives plus platforms such as Databricks and the GenAI Gateway, and apply MLOps for automation, continuous delivery, and compliance with AI/ML control expectations.\nNEO is the firm’s agent runtime: it gives agents secure execution, agent-to-agent (A2A) communication, MCP-based tool access, a managed memory layer, and permission-aware, auditable operation in a regulated environment. Your job is to turn that platform into shipped agents.\nJob Responsibilities\nDesign and ship production agents on NEO across the federated portfolio, owning them from prototype through production.\nBuild retrieval that holds up in production: chunking, ranking, and grounding strategies that keep answers accurate and auditable.\nDesign agent memory: episodic and semantic memory organized as memory nodes, with recall, summarization, and decay policies tuned per use case.\nOwn organizational context management - assembling entitlement-, lineage-, and tenant-aware context so each agent reasons over only what it’s allowed to see.\nCompose multi-agent workflows using A2A, and integrate tools and data through MCP servers (Bitbucket, Confluence, Databricks, Kubernetes, Snowflake, Splunk).\nBuild and run evals: task-level and end-to-end agent evaluations, regression suites, LLM-as-judge, and quality/safety gating before release.\nDeploy and operate solutions on public cloud (AWS and/or Azure) with strong SDLC, security, resiliency, and observability practices.\nPartner with product and business partners across the Corporate & Investment Bank and Payments to turn use cases into shipped, supported agents.\nRequired Qualifications, Capabilities, and Skills\nMS in Computer Science, Statistics, Mathematics, Machine Learning, or related field (or equivalent experience).\nMinimum 7 years of development experience, with at least 4 years working on AI/ML solutions.\nHands-on experience building LLM-powered or agentic applications in production, including tracing, evaluations, and guardrails.\nStrong programming skills in Python, with deep knowledge of data structures, algorithms, machine learning, data mining, information retrieval, and statistics.\nPractical RAG experience - retrieval quality, embeddings, and vector stores.\nExpert knowledge of at least one of: AWS, Azure, Kubernetes.\nKnowledge of data management and data model design; real-time processing using both SQL (e.g., Postgres) and NoSQL stores (e.g., OpenSearch, Redis).\nExcellent communication skills with the ability to partner effectively with senior technical and business stakeholders.\nPreferred Qualifications, Capabilities, and Skills\n Graph RAG experience (e.g., combining knowledge-graph traversal with vector search).\nExperience with agent frameworks or runtimes, A2A, or MCP.\nAgent memory design (memory nodes, episodic/semantic memory) and organizational context management.\nKnowledge graphs and graph databases used for retrieval.\nUnderstanding of LLM fine-tuning and small language model inference.\nAbility to develop full-stack products using modern JavaScript/TypeScript frameworks (e.g., Next.js, Svelte) for agent UIs (AG-UI / NEO UI SDK).\nExperience working in the financial or payments domain at a large institution (Investment Banking, Markets, Securities Services, or adjacent).\nKnowledge of high-performance languages such as Go or Rust.","description_format":"text","description_chars":4373,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Commercial & Retail Banks","Wealth Management & Financial Advisors","Asset Management & Funds","Investment Banking & M&A Advisory"],"lifecycle":[{"event":"open","at":"2026-10-10T14:27:56Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 3,429 · green card filings: 933","filings_12m":3429,"filings_prev_12m":3601,"green_card_filings_12m":933,"median_offered_wage_usd":160366,"route":null,"cap_exempt":false,"checked_at":"2026-10-03T21:08:04+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":2086}],"liveness":{"score":71,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.787,"p_room":0.9,"age_days":4,"expected_fill_days":10,"reasons":["conf:2","win:mid","comp:brand"],"computed_at":"2026-10-13T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/jpmorganchase-lead-machine-learning-engineer-agentic-pricing","json_url":"https://alion.io/job/jpmorganchase-lead-machine-learning-engineer-agentic-pricing.json","meta":{"generated_at":"2026-10-14T00:30:49Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":721,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-15T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":257},"rest":"https://alion.io/mcp/rest/get_company?id=257"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fjpmorganchase-lead-machine-learning-engineer-agentic-pricing"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fjpmorganchase-lead-machine-learning-engineer-agentic-pricing"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fjpmorganchase-lead-machine-learning-engineer-agentic-pricing"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/jpmorganchase-lead-machine-learning-engineer-agentic-pricing\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fjpmorganchase-lead-machine-learning-engineer-agentic-pricing"}]}