{"id":611481,"url":"https://alion.io/job/realpage-ai-security-engineer-iii-2","title":"AI Security Engineer III","company":{"id":20073,"name":"RealPage","domain":"realpage.com","url":"https://alion.io/company/realpage","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"iCIMS","truth_index":{"grade":"A","score":98,"open_postings":9,"ghost_share":0,"stale_share":0,"repost_share":0.111,"time_to_fill_p50_days":22,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Security","role_family":"Security","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19500,"max_usd":49000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":22},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Claude Code","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"EU AI Act","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Gemini","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Llama","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Mistral","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"NIST AI RMF","optional":false},{"name":"OpenAI","optional":false},{"name":"OWASP Top 10","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"ServiceNow","optional":false}],"status":"live","first_seen_at":"2026-09-10T18:14:05Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-11-05T00:04:10Z","board_verified":true,"closed_at":null,"days_open":55,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":54},"description":"Overview\nThis role reports into Director/Sr. Manager within Technology GRC and is the technical builder behind the function's agentic AI transformation. The AI Security Engineer III designs, builds, and operates the AI agents and automations that deliver GRC services - with primary focus on the GRC Tool platform, Technology Risks, Threats and Controls Library, the Risk Register, and Policy Governance - all operating under a human-in-the-loop model supervised by the responsible GRC leader. The role bridges GRC domain requirements and engineering execution, prototyping control automations, evidence collectors, and governance tooling that reduce manual effort and enable the team to scale without proportional headcount growth.Responsibilities\nGRC Tool & Automation EngineeringBuild and integrate agentic AI solutions and automations within the enterprise GRC platform to standardize workflows, automate evidence collection, and improve reporting.\nDevelop control automations, evidence collectors, and governance tooling, reducing dependence on the broader engineering backlog.\nRisk Register AutomationEngineer AI-assisted workflows to populate, maintain, and reconcile the enterprise Risk Register across technology domains.\nAutomate linkage between risk entries, controls, and remediation tracking.\nPolicy Governance AutomationBuild AI-assisted tooling for policy drafting, framework crosswalks, annual review cadence, and exception workflows.\nAgent Design, Safety & Operations (Human-in-the-Loop)Design agentic workflows using RAG, function/tool calling, and Model Context Protocol (MCP), with appropriate guardrails for accuracy, confidentiality, and IP boundaries.\nImplement human-in-the-loop checkpoints and monitoring so GRC leaders can supervise and validate agent outputs.\nApply AI risk controls aligned to OWASP Top 10 for LLM Applications, NIST AI RMF, ISO/IEC 42001, and MITRE ATLAS.\nAgent Evaluation, Observability & GuardrailsBuild evaluation harnesses and observability for deployed agents - measuring grounding, accuracy, and consistency while minimizing hallucinations across GRC use cases.\nImplement guardrails, deployment gates, and immutable audit trails/logging so non-compliant or low-confidence outputs are caught before use.\nMaintain model documentation (model cards, data provenance) to support AI governance and regulatory defensibility.\nQualifications\nBachelor's degree in Computer Science, Software Engineering, Data Science, or a related field; equivalent practical experience considered.\nMinimum 4+ years in software/AI engineering, with hands-on experience building LLM-powered applications and agentic workflows.\nProficiency in Python (or comparable) and modern AI development tooling (e.g., Claude Code, Cursor, GitHub Copilot).\nHands-on experience with LLM application patterns - prompt engineering, RAG, function/tool calling, agentic orchestration, and MCP.\nFamiliarity with leading LLMs (Anthropic Claude, OpenAI GPT/o-series, Google Gemini, Meta Llama, Mistral) and model selection trade-offs (reasoning depth, context window, cost, latency, data residency).\nWorking knowledge of the AI/LLM risk landscape: OWASP Top 10 for LLM Applications, NIST AI RMF, ISO/IEC 42001, MITRE ATLAS, and emerging regulation (EU AI Act, NYDFS AI guidance).\nExperience integrating with enterprise platforms and APIs; familiarity with GRC tooling (e.g., ServiceNow IRM, Archer, AuditBoard) a plus.\nAbility to translate GRC domain requirements into well-governed, production-grade automations with human-in-the-loop controls.\nStrong collaboration skills and the ability to partner with non-technical GRC stakeholders.\nExperience building agent evaluation frameworks, guardrails, prompt/version management, and observability/logging for production LLM systems.\nFamiliarity with cloud ML platforms (AWS Bedrock/SageMaker, Azure AI, GCP Vertex) and CI/CD-integrated deployment gates.\nAI governance certification a plus (e.g., IAPP AIGP), including agentic architecture concepts.\nPreferred experience in the Property Management, Multifamily Housing, SaaS, FinTech, or PropTech 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