{"id":1147320,"url":"https://alion.io/job/ivanti-staff-applied-ai-engineer-2","title":"Staff Applied AI Engineer","company":{"id":52544,"name":"Ivanti","domain":"ivanti.com","url":"https://alion.io/company/ivanti","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["South Jordan, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":142000,"max_usd":286000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":844},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"CrewAI","optional":false},{"name":"Hybrid Search","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LLMOps","optional":false},{"name":"OpenAI Agents SDK","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Reranking","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"GCP","optional":true},{"name":"LangChain","optional":true},{"name":"Quantization","optional":true},{"name":"TensorRT","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-09-23T07:39:32Z","employer_posted_date":"2026-09-23","last_verified_at":"2026-10-24T08:41:05Z","board_verified":true,"closed_at":null,"days_open":31,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":31},"description":"About Us\nIvanti empowers organisations to manage and secure technology smarter through our AI-powered Ivanti Neurons platform. We help IT and Security teams reduce complexity, work proactively, and deliver better outcomes at scale for customers around the world.\nIvanti helps organisations work smarter through Autonomous Endpoint Management powered by our AI-driven Ivanti Neurons platform-delivering better outcomes for our customers by reducing complexity and enabling proactive IT and security operations.\nAbout the Role \nWe're looking for a rare, full-stack data and AI practitioner who can operate fluidly from raw data all the way to production AI systems and the enterprise architecture that supports them. You will ingest and reason over everything from highly structured warehouse data in Snowflake to messy unstructured sources, turn it into defensible analytics, and ship agentic AI solutions that are both intelligent and ruthlessly cost-efficient. \nThis is a builder-first role with real architectural ownership. You'll write the models and the agents yourself, and you'll define the reference architectures, patterns, and standards that let the rest of the organization build on top of your work. If you're equally comfortable defending a confidence interval and a system-design decision, this role is for you. \nWhat You'll Do \n Unify structured and unstructured data. Build pipelines that pull structured data from Snowflake (and adjacent warehouses/lakes) alongside unstructured sources - text, documents, logs, transcripts - into clean, modeling-ready datasets. \n Deliver decision-grade analytics. Produce customer churn analytics with properly quantified uncertainty (confidence/credible intervals), not just point estimates, and communicate what the numbers can and can't support. \nBuild predictive and prescriptive models. Move beyond \"what will happen\" to \"what should we do about it\" - forecasting, propensity, and optimization/recommendation systems that drive concrete business actions. \nEngineer agentic AI systems. Design and ship LLM-powered agents and workflows that are token-efficient by design - tight context management, retrieval and caching strategies, model routing, and evaluation harnesses that keep cost and latency low without sacrificing quality. \nArchitect for the enterprise. Define reference architectures, integration patterns, and governance standards spanning data ingestion, model development, MLOps/LLMOps, security, and observability - and bring stakeholders along with clear diagrams and documentation. \nOwn quality and reliability. Establish evaluation, monitoring, and guardrails for drift, accuracy, bias, safety, and cost across both classical ML and GenAI systems. \nPartner across the business. Translate ambiguous business problems into technical solutions and explain technical tradeoffs to non-technical stakeholders. \nWhat You Bring (Required) \nStrong hands-on data engineering with Snowflake (modeling, performance, cost management) and SQL, plus experience wrangling unstructured data. \nSolid applied statistics: you can build churn/retention models and correctly express uncertainty with confidence or credible intervals, and you understand the assumptions behind them. \nDemonstrated experience building predictive and prescriptive analytics that shipped and influenced decisions. \nProduction experience with LLM/agentic systems - frameworks such as LangGraph, the Claude Agent SDK, CrewAI, or custom orchestrators - with a real track record of optimizing for token efficiency, cost, and latency. \nProduction RAG experience (chunking, hybrid search, reranking, retrieval evals) is strongly expected at the senior+ level. \n Architecture chops: you can design and document end-to-end systems and patterns others build on, and defend those decisions with evidence. \nStrong Python and a software-engineering mindset (testing, version control, CI/CD). \nExcellent written and verbal communication; comfort working asynchronously in a distributed team. \nNice to Have (Preferred) \nCloud certifications (AWS Solutions Architect, Google Cloud Professional ML Engineer, Azure AI Engineer) and/or TOGAF for enterprise architecture. \nExperience with inference optimization (quantization, model routing, caching, vLLM/TensorRT-style serving). \nMLOps/LLMOps tooling and platform-building experience. \nDomain experience in [your industry], and prior work owning AI strategy or build-vs-buy decisions. \nWhat Success Looks Like (First 6-12 Months) \nA unified data foundation that combines Snowflake and unstructured sources for downstream modeling. \nA churn analytics product trusted by the business, with quantified uncertainty and clear recommended actions. \nAt least one production agentic solution that demonstrably reduces token spend/latency versus a naive baseline while meeting quality bars. \nA documented reference architecture and set of standards adopted by other teams. \nWhy Ivanti?\nFriendly flexible working model: Empower excellence whether you’re at home or in the office and support work-life balance.\nCompetitive compensation & total rewards: Including health, wellness, and financial plans tailored for you and your family.\nGlobal, diverse teams: Collaborate with talented people from 23+ countries.\nLearning & development: Grow your skills with access to best-in-class learning tools and programs.\nEquity & belonging: We value every voice. Your story helps inform our solutions for a changing world.\nWhat drives us\nIvanti’s mission is to elevate human potential within organizations by managing, protecting and automating technology for continuous innovation.\nIt is through diverse and inclusive hiring, decision-making, and commitment to our employees and partners that we will continue to build and deliver world-class solutions for our customers.\nTo learn more about Ivanti’s Mission and Core Values. \nInclusion at Ivanti\nIvanti is proud to be an Equal Opportunity Employer. We’re committed to building a diverse team and fostering an inclusive environment where everyone belongs. We welcome applicants from all backgrounds and walks of life. Need adjustments during the process? 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