{"id":3251015,"url":"https://alion.io/job/infor-business-analyst","title":"Business Analyst","company":{"id":1808,"name":"Infor","domain":"infor.com","url":"https://alion.io/company/infor","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Pinpoint","truth_index":{"grade":"A","score":100,"open_postings":5,"ghost_share":0,"stale_share":0,"repost_share":0.2,"time_to_fill_p50_days":9,"computed_at":"2026-10-26T05:57:25Z"}},"role":"Analytics","role_family":"Analytics","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Atlanta, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":74000,"max_usd":167000,"period":"year","method":"role_country_seniority_unknown","sample_n":5687},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Function Calling","optional":false},{"name":"Hallucination","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":true},{"name":"Model Context Protocol","optional":true}],"status":"live","first_seen_at":"2026-10-24T21:26:15Z","employer_posted_date":"2026-10-24","last_verified_at":"2026-10-26T09:04:56Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Infor is seeking a Business Analyst to help shape the next generation of adaptive and agentic experiences across Infor applications. You will be the bridge between business stakeholders, product teams, UX, and engineering on GenAI initiatives, turning complex business needs into clear requirements, user stories, and testable specifications for AI agents and LLM-based features. You will define what an agent should do, which tools and data it can use, where it must hand off to a person, and how its quality will be judged, and you will help drive stakeholder alignment and delivery. This is a non-coding role for someone who is technically comfortable and has worked on GenAI or agentic initiatives.\nA Typical Day in the Life Includes:\nGathering, analyzing, prioritizing, and documenting business and functional requirements from stakeholders across multiple teams \nCollaborating with product managers, engineers, architects, and UX teams to define AI-enabled solutions and adaptive user experiences \nTranslating business workflows and user needs into user stories, acceptance criteria, rules, and application logic \nResearching comparable products, features, and agentic approaches to inform prioritization and scoping \nPlanning and coordinating requirements activities for product initiatives focused on GenAI, agentic experiences, and cloud-based solutions \nValidating solutions across cloud suites and cross-functional teams to ensure business and technical requirements are met \nDriving stakeholder alignment and obtaining buy-in on product requirements, priorities, and solution approaches \nCreating documentation, release notes, presentations, and other artifacts that support successful product delivery\nBasic Qualifications:\nExperience gathering and documenting requirements, user stories, and acceptance criteria.\nExperience analyzing workflows and translating them into clear business rules or system logic.\nWorking understanding of how LLMs and AI agents behave (prompting, tool use, retrieval, and failure modes such as hallucination), and the ability to turn that understanding into testable requirements. \nHands-on experience with at least one GenAI, LLM, agentic, or conversational AI initiative, as a business analyst, product owner, or equivalent. \nAbility to read API documentation and follow architecture-level discussion well enough to write requirements that are technically coherent, without needing to write code. \nBaseline AI literacy: understands how AI works and where it can go wrong, recognizes where it's useful, can direct it effectively, evaluates its outputs before relying on them, and uses it responsibly. \nUses AI tools in day-to-day analysis and documentation work (for example, drafting stories or summarizing research) and checks the output before relying on it. \nExperience creating documentation, release notes, or other product-related deliverables\nLegal authorization to work permanently in the United States for any employer without requiring a visa transfer or visa sponsorship now or in the future.\nPreferred Qualifications:\nIndustry domain knowledge in manufacturing, distribution, healthcare, hospitality, public sector, or other enterprise industries\nFamiliarity at a conceptual level with Model Context Protocol (MCP), tool calling, or agent frameworks\nExperience defining evaluation criteria or test scenarios for AI features\nAwareness of responsible-AI concerns such as explainability, auditability, and guardrails \nExperience with conversational design, prototyping, or close collaboration with 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