{"id":1214137,"url":"https://alion.io/job/jpmorganchase-sr-lead-software-engineer-ai-agents","title":"Sr Lead Software Engineer - AI Agents","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":99,"open_postings":546,"ghost_share":0.013,"stale_share":0.136,"repost_share":0.114,"time_to_fill_p50_days":8,"computed_at":"2026-10-19T05:45:15Z"}},"role":"Backend","role_family":"Backend","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":["Buenos Aires, Argentina"],"countries":["AR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":61000,"max_usd":183000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1965},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Function Calling","optional":false},{"name":"Go","optional":false},{"name":"GraphRAG","optional":false},{"name":"Hallucination","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Java","optional":false},{"name":"LangGraph","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LLMOps","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"ServiceNow","optional":false},{"name":"Snowflake","optional":false},{"name":"Tool Use","optional":false},{"name":"TypeScript","optional":false},{"name":"LangChain","optional":true},{"name":"Service Desk","optional":true}],"status":"live","first_seen_at":"2026-08-06T14:44:41Z","employer_posted_date":"2026-08-06","last_verified_at":"2026-10-19T14:26:33Z","board_verified":true,"closed_at":null,"days_open":74,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":73},"description":"We are building a portfolio of agentic operations - production-grade AI agents that plan, act, and continuously improve the everyday experiences of our employees. The mission is to eliminate friction from the moments that matter employees spend more time on work that matters and less time on tickets, forms, and queues.\nAs Senior Lead Software Engineer, AI Engineering, you will be a hands-on senior individual contributor on this team, reporting to the Executive Director who owns the agentic platform and flagship agents. You will be the technical anchor of one or more agent squads: designing the agent, writing the code, running the evaluation harness, integrating with enterprise tools (ServiceNow, Databricks, identity, endpoint), and taking the pager when it ships.\nYou will pair with engineers, review PRs, drive design docs, mentor the squad, and be personally accountable for the correctness, safety, cost, and business impact of the agents you build.\nJob responsibilities\nDesign and build agents\nOwn the end-to-end design of production agents: planner, tools, memory, retrieval (RAG / GraphRAG), guardrails, human-in-the-loop, evaluators.\nImplement using the team's Model Context Protocol (MCP) stack - write MCP servers/clients, define tool schemas, negotiate capabilities, and integrate securely with enterprise systems.\nChoose the right orchestration pattern (single-agent, planner-executor, supervisor-worker, debate/critique) for each use case; reject unnecessary complexity.\nEvaluation, safety, and quality\nBuild and maintain the evaluation harness for your agents: gold sets, offline benchmarks, LLM-as-judge with human calibration, online A/B, regression gates in CI/CD.\nInstrument every agent with business KPIs (deflection rate, time-to-resolve, CSAT, cost per interaction) and quality KPIs (task success, groundedness, refusal correctness, safety incidents).\nPartner with cyber, privacy, and model risk to make guardrails concrete: PII handling, prompt-injection & jailbreak defense, tool-use hygiene, secret handling, prompt/model version pinning.\nProduction reliability (SRE for agents)\nOwn SLOs and error budgets for your agents; write runbooks; take part in the on-call rotation.\nBuild canaries, circuit breakers, deterministic replay, and rollback paths for prompts, models, and tools.\nDiagnose and fix production issues end-to-end - from token spend anomalies to tool call failures to hallucination regressions.\nPlatform contribution\nContribute to the shared agentic platform (orchestration, model gateway, vector/knowledge stores, telemetry, eval harness) - not just consume it. Push improvements upstream so other squads benefit.\nWrite design docs, patterns, and internal blog posts. Represent the team in architecture reviews.\nTechnical leadership without being a manager\nSet the technical bar in your squad through code reviews, pairing, and design reviews.\nMentor mid-level and junior engineers; grow the next generation of AI engineers.\nInterview candidates and help sustain a strong hiring bar.\nRequired qualifications, capabilities and skills\n8+ years of software engineering experience, with 2+ years shipping production LLM- or agent-based systems to real users (not just prototypes or notebooks).\nDeep hands-on expertise in Python (primary) and comfort with at least one other modern language (TypeScript / Java / Go).\nPractical, current experience with the agentic stack: LLM orchestration (e.g. LangGraph, LlamaIndex, Semantic Kernel, custom), tool/function calling, RAG, evaluation harnesses, guardrails, prompt & model versioning, model gateways.\nHands-on with Model Context Protocol (MCP) architectures - designing servers/clients, tool schemas, capability negotiation, and secure enterprise deployment patterns.\nTrack record of building and running production-grade backend / distributed systems (APIs, queues, workers, observability, on-call).\nStrong grounding in data platforms (Databricks / Snowflake / lakehouse patterns) and modern MLOps/LLMOps (CI/CD, feature/prompt/model registry, telemetry).\nPractical experience with responsible AI, security, and controls for enterprise deployments: PII handling, red-teaming, prompt-injection defense, secret & tool-use hygiene.\nClear technical communication: you can write a crisp design doc, review a PR with substance, and explain a trade-off to a non-technical stakeholder.\nBachelor's in Computer Science or related discipline, or equivalent industry experience.\nPreferred qualifications, capabilities and skills\nExperience building employee-facing / workforce productivity products at scale (IT service desk, HR tech, knowledge management, workplace assistants).\nExperience integrating with ServiceNow, identity providers, endpoint management, and enterprise search.\nExperience with multi-agent patterns (planner-executor, supervisor-worker, debate/critique) and long-horizon workflows.\nContributions to open source (especially in the MCP / agent / eval ecosystem), published research, patents, or public talks in AI / agents / SRE.\nPrior experience in a highly regulated environment (financial services, healthcare, public sector) with model risk management (SR 11-7 or equivalent).\nMaster's or PhD in a quantitative discipline.","description_format":"text","description_chars":5225,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Wealth Management & Financial Advisors","Asset Management & Funds","Investment Banking & M&A Advisory"],"lifecycle":[{"event":"open","at":"2026-09-25T06:58:26Z"},{"event":"close","at":"2026-09-25T14:57:18Z"},{"event":"reopen","at":"2026-09-26T21:12:26Z"},{"event":"close","at":"2026-09-27T00:28:19Z"},{"event":"reopen","at":"2026-09-27T16:36:02Z"},{"event":"close","at":"2026-09-28T13:45:22Z"},{"event":"reopen","at":"2026-09-29T03:08:11Z"},{"event":"close","at":"2026-09-29T21:51:58Z"},{"event":"reopen","at":"2026-09-30T07:48:16Z"}],"visa":[],"liveness":{"score":7,"band":"cold","label":"Long shot","p_open":1,"p_active":0.251,"p_room":0.28,"age_days":73,"expected_fill_days":8,"reasons":["conf:0","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-19T05:45:15Z"},"pay":null,"html_url":"https://alion.io/job/jpmorganchase-sr-lead-software-engineer-ai-agents","json_url":"https://alion.io/job/jpmorganchase-sr-lead-software-engineer-ai-agents.json","meta":{"generated_at":"2026-10-19T15:30:48Z","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":11541,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-20T00:00:00Z"}},"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-sr-lead-software-engineer-ai-agents"},{"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-sr-lead-software-engineer-ai-agents"},{"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-sr-lead-software-engineer-ai-agents"},{"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-sr-lead-software-engineer-ai-agents\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fjpmorganchase-sr-lead-software-engineer-ai-agents"}]}