{"id":1230331,"url":"https://alion.io/job/httpswww-linkedin-comcompanyhire3-global-senior-agentic-ai-engineer","title":"Senior Agentic AI Engineer","company":{"id":3800189,"name":"https://www.linkedin.com/company/hire3-global/","domain":"hire3global.com","url":"https://alion.io/company/httpswww-linkedin-comcompanyhire3-global","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":"senior","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":32000,"max_usd":82000,"period":"year","method":"role_seniority_country_cell","sample_n":10},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Apache Kafka","optional":false},{"name":"API Gateway","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"Chain-of-Thought","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"FastAPI","optional":false},{"name":"Function Calling","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RabbitMQ","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Structured Outputs","optional":false},{"name":"WebSockets","optional":false},{"name":"DPO","optional":true},{"name":"DSPy","optional":true},{"name":"Fine-tuning","optional":true},{"name":"HIPAA","optional":true},{"name":"LoRA","optional":true},{"name":"Machine Learning","optional":true},{"name":"PEFT","optional":true},{"name":"Post-training","optional":true},{"name":"RLHF","optional":true},{"name":"TGI","optional":true},{"name":"Triton","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-09-19T06:33:18Z","employer_posted_date":null,"last_verified_at":"2026-09-19T06:33:18Z","board_verified":false,"closed_at":null,"days_open":7,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":7},"description":"Senior Agentic AI Engineer\n\nLocation : Hyderabad\n\nRole Overview : \n\nAs an Agentic AI Engineer, you'll design, build, and ship LLM-powered, agentic AI systems that run in production at scale. You won't just prototype you'll own pipelines end-to-end, from prompt design and eval frameworks to distributed microservice deployment and monitoring. You'll take full ownership of everything you build, including end-to-end testing, so that what ships is production-ready, reliable, and safe from day one.\n\nKey Responsibilities : \n\n- Design and build LLM-powered agentic AI pipelines that reason, plan, and execute multi-step workflows with minimal human intervention.\n\n- Own tool and function calling integrations connect LLMs to internal APIs, EHR systems, calendars, and third-party services.\n\n- Build and maintain rigorous eval frameworks : offline eval sets, regression suites, latency benchmarks, and safety/guardrail tests.\n\n- Ship and operate LLMs in production : streaming responses, structured outputs, prompt versioning, cost/latency tracking, and observability.\n\n- Architect and maintain distributed microservices that expose LLM APIs async Python (FastAPI), event-driven pipelines, and real-time WebSocket workflows.\n\n- Build RAG pipelines : chunking strategies, embeddings, vector stores, retrieval tuning, and PHI-safe handling.\n\n- Take full ownership and conduct end-to-end testing for everything you build from unit and integration tests through to production validation and post-deployment monitoring.\n\n- Collaborate closely with product, backend, and QA to define AI requirements and ship reliable, safe features.\n\nQualifications : \n\n- 3+ years of hands-on Gen AI / LLM engineering experience building and shipping real systems, not just research or prototypes.\n\n- 5+ years of hands-on AI / ML engineering experience overall (Gen AI + pre-Gen AI combined).\n\n- Deep LLM expertise in prompt engineering, tool/function calling, structured outputs, chain-of-thought, and agent orchestration (LangChain, LangGraph, or similar).\n\n- Proven eval culture that you treat evals as a first-class concern not an afterthought.\n\n- Production LLM experience, integrations with OpenAI / Azure OpenAI / AWS Bedrock, streaming, cost optimisation, and monitoring.\n\n- Strong software engineering fundamentals in Python (strong), async programming, REST APIs, CI/CD, Docker.\n\n- Distributed systems fluency with microservice design, event-driven architecture (Kafka/SQS/RabbitMQ), and LLM API gateway patterns.\n\n- End-to-end ownership mindset, you write tests, validate in staging, and don't consider a feature done until it's verified in production.\n\nPreferred Skills : \n\n- LLM post-training experience with fine-tuning, RLHF, DPO, or LoRA for domain-adapted or instruction-tuned models.\n\n- Automatic prompt optimisation familiarity with tools or techniques like DSPy, TextGrad, or automated prompt search for systematic prompt improvement.\n\n- Healthcare industry experience, working knowledge of EHR systems, HL7/FHIR standards, HIPAA compliance, or clinical workflows.\n\n- Startup experience where you've worked in a fast-moving, resource constrained environment where you wore multiple hats and shipped quickly.\n\n- Scaling and on-prem deployments experience deploying LLMs at scale, including self-hosted / on-prem model serving (vLLM, TGI, Triton) or hybrid cloud architectures.\n\nSkills\nPython, Machine Learning, Generative AI, LangChain, FastAPI, LangGraph, Agentic AI, Artificial Intelligence, LLM, OpenAI, LORA","description_format":"text","description_chars":3505,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-25T14:00:00Z"}],"liveness":{"score":80,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.798,"p_room":1,"age_days":6,"expected_fill_days":24,"reasons":["seen:6","win:early"],"computed_at":"2026-09-26T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/httpswww-linkedin-comcompanyhire3-global-senior-agentic-ai-engineer","json_url":"https://alion.io/job/httpswww-linkedin-comcompanyhire3-global-senior-agentic-ai-engineer.json","meta":{"generated_at":"2026-09-27T01:02:19Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":952,"day_limit":5000,"remaining_today":4048,"minute_limit":60,"resets_at":"2026-09-28T00:00:00Z"}}}