{"id":4196155,"url":"https://alion.io/job/recruitbots-ai-agentic-ai-engineer","title":"Agentic AI Engineer","company":{"id":4481205,"name":"RecruitBots AI","domain":"recruitbots.ai","url":"https://alion.io/company/recruitbots-ai","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","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":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"JavaScript","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"TypeScript","optional":false},{"name":"Docker","optional":true},{"name":"FastAPI","optional":true},{"name":"Kubernetes","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Redis","optional":true}],"status":"live","first_seen_at":"2026-11-12T17:24:32Z","employer_posted_date":null,"last_verified_at":"2026-11-12T17:24:32Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"How to apply\nApply through Linked-In Easy Apply then login to https://candidate.recruitbots.ai/utm_source=aae-ms-r-i. More detailed instructions on onboarding.\n\nCompany: RecruitBots AI\nLocation: Remote · India\nExperience: 3–6 years\nType: Full-time\nSalary: 12–22 LPA\nAbout the role\nWe are looking for an Agentic AI Engineer with 3–6 years of experience to design, build, and improve AI systems that can plan and execute multi-step tasks using tools, APIs, and external data sources.\nYou will work with engineering and product teams to develop reliable agentic workflows, integrate LLMs with business systems, and evaluate agent behavior in real-world scenarios. The role involves hands-on engineering across orchestration, tool use, memory, retrieval, and production reliability.\nResponsibilities\nDesign and develop AI agents capable of executing multi-step tasks and coordinating tools or services.\nBuild agent workflows using frameworks such as LangGraph, LangChain, AutoGen, or equivalent\ntechnologies.\nImplement tool/function calling, workflow orchestration, state management, memory, and human-in-the-loop controls.\nIntegrate agents with REST APIs, databases, internal platforms, and third-party services.\nDevelop RAG pipelines and retrieval components to ground agent responses in relevant data.\nCreate guardrails, validation steps, fallback paths, and error-handling mechanisms for reliable execution.\nEvaluate agent performance across task completion, accuracy, latency, reliability, and cost.\nDebug tool failures, looping behavior, incorrect outputs, and orchestration issues.\nCollaborate with product and engineering teams to move prototypes into secure, scalable production systems.\nRequired Skills\n3–6 years of experience in software engineering, AI engineering, or a closely related role.\nStrong programming skills in Python; familiarity with JavaScript/TypeScript is an advantage.\nHands-on experience building LLM-powered applications and integrating model APIs.\nPractical understanding of AI agents, tool calling, multi-step workflows, and orchestration patterns.\nExperience with at least one agent framework such as LangGraph, LangChain, or AutoGen.\nUnderstanding of RAG, embeddings, vector databases, and retrieval strategies.\nExperience with APIs, backend services, debugging, and version control.\nAbility to evaluate and improve the reliability of LLM-driven systems.\nGood to Have\nExperience with multi-agent systems, planning, routing, reflection, or agent collaboration patterns.\nKnowledge of observability and evaluation tools for LLM applications.\nExperience with FastAPI, Docker, Kubernetes, or cloud deployment.\nFamiliarity with Redis, PostgreSQL, MongoDB, or vector databases.\nExperience implementing authentication, permissions, guardrails, and secure tool execution.\nEducation\nBachelor's degree in Computer Science, Information Technology, Engineering, or a related field.\nStrong hands-on agentic AI projects and production implementation experience are highly valued.\nWhat We're Looking For\nAbility to design agents that solve concrete workflows rather than add unnecessary complexity.\nStrong debugging skills and a systematic approach to investigating unpredictable model behavior.\nGood judgment around autonomy, validation, and when human approval is required.\nOwnership of performance, reliability, and maintainability.\nAbility to collaborate across product and engineering teams in a fast-moving 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