{"id":1218328,"url":"https://alion.io/job/ey-ai-systems-engineer-devops-observability-senior","title":"AI Systems Engineer - DevOps& Observability - Senior","company":{"id":2859,"name":"Ernst & Young","domain":"ey.com","url":"https://alion.io/company/ey-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Fort Worth, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":106900,"max":176500,"currency":"USD","period":"year","gross":null,"usd_annual":176500},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"ArgoCD","optional":false},{"name":"CI/CD","optional":false},{"name":"CVE","optional":false},{"name":"FinOps","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"GitOps","optional":false},{"name":"Grafana","optional":false},{"name":"Harbor","optional":false},{"name":"Hugging Face","optional":false},{"name":"Jaeger","optional":false},{"name":"JFrog Artifactory","optional":false},{"name":"Langfuse","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"Loki","optional":false},{"name":"Mimir","optional":false},{"name":"MLFlow","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prometheus","optional":false},{"name":"Ray","optional":false},{"name":"Ray Serve","optional":false},{"name":"SBOM","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Triton","optional":false},{"name":"Trivy","optional":false},{"name":"vLLM","optional":false},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-09-25T02:01:00Z","employer_posted_date":"2026-09-25","last_verified_at":"2026-09-29T00:20:34Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Location: Anywhere in Country\nAt EY, we’re all in to shape your future with confidence.\nWe’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.\nThe opportunity\nWe are seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. These are the systems that ship, run, and make fully visible every AI workload. Within the Hybrid AI Multi-Environment Runtime (HAI), this role advised how AI services and agents are built and deployed, how models execute, how requests are routed to them, how AI assets are catalogued and governed, how consumption is measured and bounded, and how the entire platform is observed across cloud, on-prem, edge, and air-gapped environments. Works with senior engineers to test and develop capabilities.\nThis is a distinct discipline from platform, data, and trust engineering. Where Platform Engineering owns the cluster substrate and its infrastructure automation, this role owns the delivery and runtime surface, including the CI/CD/CV pipelines that ship AI workloads, secure model execution, semantic routing, and model/prompt selection, together with the governance, discovery, cost, and telemetry systems that keep AI workloads shippable, economical, discoverable, and transparent. It sits at the intersection of DevOps, MLOps, FinOps, and observability.\nThis role is ideal for an engineer who is equally comfortable building automated delivery pipelines, operating high-performance inference (GPUs, model servers, sandboxed execution), and building deep observability and cost visibility; who understands that in regulated contexts every AI workload must be delivered repeatably and every AI request must be economically bounded, attributable, and traceable end-to-end.\nYour key responsibilities\n Supports DevOps and delivery for AI workloads: build and operate the CI/CD/CV pipelines that ship AI services, agents, and runtime components, including automated build, test, continuous verification, release, and rollback, so AI workloads are delivered repeatably and safely into every environment.\nOwn governance and discovery for AI assets, including service catalog/registry (Artifactory/Nexus, Harbor), experiment tracking and model metadata (MLflow), upstream registries/mirrors (HuggingFace/NGC), CVE/SBOM scanning (Trivy), lineage contracts (OpenLineage), and license management.\nOwn resource and cost management, including quotas and rate limits, cost attribution and utilization (Apptio/OpenCost/Kubecost), so AI execution stays economically bounded and controllable per tenant and engagement.\nOwn the full observability stack, including metrics (Prometheus/Mimir), logs (Loki), traces (Tempo/Jaeger), dashboards (Grafana), LLM debugging and evaluation (LangSmith/Langfuse), and SLA/alert notifications.\nOwn the OpenTelemetry collection layer, including multi-tenant receiver, exporters and queues (Kafka sink), DCGM exporter for GPU telemetry, processor batching, and dynamic filtering, so every signal is captured and routed reliably.\nAutomate GitOps-based delivery and continuous verification; embedding quality, integrity, and cost gates into pipelines so releases are policy-compliant by default rather than by manual review.\nClose the loop between delivery and observability by using telemetry, evaluation, and cost signals to drive deployment decisions, progressive rollout, and automated rollback of AI workloads.\nEnsure cost and telemetry are identity-stamped and per-tenant, so consumption and behavior are attributable end-to-end, keeping FinOps and observability tied to the workloads that generate the load.\nSkills and attributes for success\nStrong DevOps expertise: CI/CD/CV pipeline design, GitOps, continuous verification, and progressive/automated release and rollback for production workloads.\nDeep expertise operating model-serving and inference systems (Ray, vLLM/Triton/NIM) on GPUs at production scale.\nDeep observability skills: metrics, logs, traces, and OpenTelemetry.\nFinOps mindset: able to attribute, bound, and optimize AI consumption cost per tenant and workload.\nFamiliarity with model/artifact governance, registries, CVE scanning, and license/lineage tracking.\nComfortable operating across cloud, on-prem, edge, and air-gapped environments with consistent runtime and telemetry semantics.\nStrong communicator able to explain runtime, cost, and observability tradeoffs to engineers, architects, and leadership.\nTo qualify you must have\n8+ years in DevOps, MLOps, platform, or observability engineering, with hands-on production ownership of AI or high-throughput services.\nStrong hands-on DevOps experience, including CI/CD/CV pipelines and GitOps tooling (ArgoCD, Helm, GitHub Actions/GitLab CI, or equivalents) for automated build, test, release, and rollback.\nHands-on expertise operating inference/model-serving frameworks (Ray Serve, vLLM, Triton, or NIM) on GPU infrastructure.\nStrong experience with observability stacks (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.\nExperience with API gateways and request routing (Envoy or equivalent), including streaming responses.\nExperience with cost management / FinOps tooling (OpenCost, Kubecost, or equivalent) and quota/rate-limit enforcement.\nFamiliarity with model/artifact registries and supply-chain scanning (Harbor, MLflow, Trivy/SBOM).\nProven track record operating AI or service infrastructure under compliance, security, or regulatory constraints.\nAbility to define clean ownership boundaries and consumption contracts with platform, trust, and data teams.\nIdeally, you’ll also have\nBachelor’s or Master’s degree in Computer Science or related technical field.\nExperience with LLM evaluation and debugging tooling (LangSmith, Langfuse) and prompt/response quality measurement.\nExperience with sandboxed/secure execution (gVisor, Firecracker, or microVM isolation) for untrusted or multi-tenant workloads.\nFamiliarity with GPU telemetry (DCGM) and GPU utilization optimization.\nExperience with lineage and governance contracts (OpenLineage) and AI license management.\nExposure to multi-tenant cost attribution and per-tenant SLA/alerting.\nExposure to regulated delivery environments (financial services, tax, healthcare, risk).\nWhat we offer you\nAt EY, we’ll develop you with future-focused skills and equip you with world-class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more.\nWe offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $106,900 to $176,500. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $128,400 to $200,600. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.\nJoin us in our team-led and leader-enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.\nUnder our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances. You’ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.\nAre you ready to shape your future with confidence? Apply today.\nEY accepts applications for this position on an on-going basis.\nFor those living in California, please click here for additional information.\nEY focuses on high-ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.\nEY | Building a better working world\nEY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.\nEnabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.\nEY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.\nEY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law.\nEY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY’s Talent Shared Services Team (TSS) or email the TSS at .","description_format":"text","description_chars":9844,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":["Flexible vacation policy"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Audit & Assurance Firms","Financial Advisory, Valuation & Restructuring","Management Consulting","Tax Advisory & Preparation"],"lifecycle":[{"event":"open","at":"2026-09-25T11:24:17Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":3,"expected_fill_days":22,"reasons":["conf:5","velocity","win:early","comp:brand"],"computed_at":"2026-09-28T05:45:00Z"},"pay":{"stated_usd_annual":176500,"is_top_pay":false},"html_url":"https://alion.io/job/ey-ai-systems-engineer-devops-observability-senior","json_url":"https://alion.io/job/ey-ai-systems-engineer-devops-observability-senior.json","meta":{"generated_at":"2026-09-29T02:28:59Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2233,"day_limit":5000,"remaining_today":2767,"minute_limit":60,"resets_at":"2026-09-30T00:00:00Z"}}}