{"id":2772126,"url":"https://alion.io/job/ust-senior-ai-engineer-agentic-ai-rag","title":"Senior AI Engineer – Agentic AI & RAG","company":{"id":1774626,"name":"UST","domain":"ust.com","url":"https://alion.io/company/ust-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"RippleHire","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":22000,"max_usd":49000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":29},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Gemini","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"IAM","optional":false},{"name":"Jenkins","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Vertex AI","optional":false}],"status":"live","first_seen_at":"2026-09-30T00:00:00Z","employer_posted_date":"2026-10-17","last_verified_at":"2026-10-18T05:36:16Z","board_verified":true,"closed_at":null,"days_open":18,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":18},"description":"We are looking for an AI Engineer with deep experience in building agent-based AI applications. This role is ideal for someone passionate about pushing the boundaries of applied AI, particularly in Retrieval-Augmented Generation (RAG), and developing production-grade intelligent systems that are secure, governed, and enterprise-ready.\nAI / LLM EngineeringDesign, develop, and deploy agent-based AI systems using LLMs.Build and scale Retrieval-Augmented Generation (RAG) pipelines for real-time and offline inference.Develop and optimize training workflows for fine-tuning and adapting models to domain-specific tasks.Collaborate with cross-functional teams to integrate knowledge bases into agent frameworks.Drive best practices in AI Engineering, model lifecycle management, and production deployment on Google Cloud (GCP).Monitor, evaluate, and improve model performance post-deployment on Google Cloud.DevOps / MLOpsImplement version control strategies using Git, manage code repositories, and ensure best practices in code management.Develop and manage CI/CD pipelines using GitHub Actions, Jenkins, or other relevant tools to streamline deployment and updates.Security & IdentitySecure AI application front-ends and user interfaces by integrating them with enterprise Single Sign-On (SSO) and Multi-Factor Authentication (MFA)OIDCOAuth 2.0SAMLIntegrate AI agent frameworks and service accounts with enterprise IGA platformsAccess provisioning\nEntitlements\nCompliance auditing\n\nCollaboration\nCommunicate technical findings and insights to non-technical stakeholders.\nParticipate in technical discussions and contribute to strategic planning.\nQualifications Education\nMaster’s / Bachelor’s degree in:Computer Science\nArtificial Intelligence\nMachine Learning\nOr a related field\n\nExperience\n10+ years of overall IT experience.\n5+ years of AI/ML Engineering experience, with a strong focus on LLM-based applications.\nProven experience building agent-based applications using Gemini, OpenAI, or similar models.\nDeep understanding of:RAG systems\nVector 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