{"id":143131,"url":"https://alion.io/job/chase-principal-software-engineer-llm-optimization","title":"Principal Software Engineer - LLM Optimization","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":535,"ghost_share":0.011,"stale_share":0.123,"repost_share":0.114,"time_to_fill_p50_days":8,"computed_at":"2026-10-17T05:46:00Z"}},"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":202000,"max_usd":413000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":691},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon EKS","optional":false},{"name":"AWQ","optional":false},{"name":"AWS","optional":false},{"name":"Chaos Engineering","optional":false},{"name":"GPTQ","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"KV Cache","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Quantization","optional":false},{"name":"SGLang","optional":false},{"name":"Speculative Decoding","optional":false},{"name":"TensorRT-LLM","optional":false},{"name":"vLLM","optional":false},{"name":"Kubernetes","optional":true},{"name":"TensorRT","optional":true}],"status":"live","first_seen_at":"2026-08-27T00:00:00Z","employer_posted_date":"2026-08-27","last_verified_at":"2026-10-17T15:34:54Z","board_verified":true,"closed_at":null,"days_open":51,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":51},"description":"At JPMorganChase, we are building the infrastructure that powers the next generation of enterprise AI - and we need the best minds in LLM inference to help us do it. This is your opportunity to work at the intersection of cutting-edge machine learning and large-scale production systems, directly influencing how one of the world's largest financial institutions deploys and optimizes AI at scale.\nAs a Principal Software Engineer at JPMorganChase within the AI/ML Data Platform team, you will serve as the firm's deepest technical voice on LLM inference performance - owning optimization strategy, benchmarking rigor, and efficiency at scale. You will work directly with senior engineering leadership to shape how our platform evolves, ensuring every model we serve is fast, cost-efficient, and production-ready. This is a high-visibility individual contributor role where your technical decisions will have direct, measurable impact on the firm's AI capabilities\nJob Responsibilities\nOwn systematic benchmarking and performance characterization across all production LLM workloads. Establish reproducible baselines, catch regressions early, and quantify the impact of every configuration change before it touches production\n\nDesign and execute quantization experiments - FP8, INT8/INT4 (GPTQ/AWQ), next-generation precision formats on current hardware - measuring accuracy delta, throughput improvement, memory reduction, and cost-per-token impact\n\nDrive speculative decoding strategy across the model portfolio: draft model, n-gram, and multi-token prediction approaches. Own acceptance rate measurement and per-workload configuration recommendations\n\nBuild and maintain a GPU efficiency scorecard: utilization, memory headroom, cost per 1K tokens, and waste identified - giving leadership a data-driven view of platform efficiency at all times\n\nBenchmark our platform against external providers and published industry numbers - know what good looks like, and close the gap\n\nLead inference engine upgrade evaluations: new scheduler architectures, async tensor parallelism, disaggregated prefill/decode, advanced speculative decoding - systematic validation before production promotion\n\nCollaborate with the EKS and disaggregated serving teams on KV-cache optimization, prefix caching strategies, and multi-node serving architecture\n\nDesign and run GPU chaos engineering: induced failure scenarios, hardware diagnostic monitoring, detection and recovery measurement\n\nArchitect and govern agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams.\n\nApply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation at scale.\n\nRequired qualifications, capabilities, and skills\nFormal training or certification on software engineering concepts and 7+ years applied experience\n\nDeep, hands-on experience with LLM inference systems - vLLM, TensorRT-LLM, SGLang, LLM-D or equivalent production serving engines\n\nStrong grasp of GPU memory architecture: KV cache sizing and dynamics, memory-bandwidth vs compute bottlenecks, the practical implications of quantization at inference time\n\nExperience with quantization techniques and their real-world tradeoffs at scale\n\nFamiliarity with speculative decoding and the variables that drive acceptance rates in production workloads\n\nRigorous benchmarking instincts - GuideLLM, custom harnesses, or equivalent. Every claim has a number behind it\n\nComfort operating in cloud GPU infrastructure at scale (AWS; EKS, managed inference services)\n\nDemonstrated awareness of the LLM inference competitive landscape, with a track record of applying industry benchmarks to drive platform improvements communicate technical trade-offs clearly to senior engineering and business stakeholders - this role presents upward regularly\n\nDemonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data.\n\nStrong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.\n\nPreferred qualifications, capabilities, and skills\nExperience with disaggregated prefill/decode serving architectures, GPU hardware diagnostics (DCGM/NVML/XID event tracking), ML observability and production monitoring\n\nFEDERAL DEPOSIT INSURANCE ACT: This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase’s review of criminal conviction history, including pretrial diversions or program entries.","description_format":"text","description_chars":5327,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"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":"2026-08-27T00:00:00Z"},{"event":"reopen","at":"2026-10-11T14:35:05Z"}],"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":"2026-10-15T11:24:14+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":10,"band":"cold","label":"Long shot","p_open":1,"p_active":0.36,"p_room":0.28,"age_days":51,"expected_fill_days":8,"reasons":["conf:0","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-17T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/chase-principal-software-engineer-llm-optimization","json_url":"https://alion.io/job/chase-principal-software-engineer-llm-optimization.json","meta":{"generated_at":"2026-10-17T15:55:42Z","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":21607,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"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%2Fchase-principal-software-engineer-llm-optimization"},{"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%2Fchase-principal-software-engineer-llm-optimization"},{"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%2Fchase-principal-software-engineer-llm-optimization"},{"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/chase-principal-software-engineer-llm-optimization\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fchase-principal-software-engineer-llm-optimization"}]}