{"id":1253509,"url":"https://alion.io/job/ionixx-technologies-lead-ai-engineer-agent-framework-agentic-applications","title":"Lead AI Engineer - Agent Framework & Agentic Applications","company":{"id":3806767,"name":"Ionixx Technologies","domain":"ionixxtech.com","url":"https://alion.io/company/ionixx-technologies","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":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":3500000,"max":4000000,"currency":"INR","period":"year","gross":true,"usd_annual":41928},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Chroma","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Context Engineering","optional":false},{"name":"Embeddings","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LangChain","optional":false},{"name":"Langfuse","optional":false},{"name":"LangGraph","optional":false},{"name":"LangSmith","optional":false},{"name":"Least Privilege","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"TypeScript","optional":false},{"name":"LLMOps","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Prompt Caching","optional":true}],"status":"live","first_seen_at":"2026-09-10T04:33:18Z","employer_posted_date":null,"last_verified_at":"2026-09-10T04:33:18Z","board_verified":false,"closed_at":null,"days_open":22,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":22},"description":"Lead AI Engineer - Agent Framework & Agentic Applications\n\nBuild Ionixx's standardized agent framework - and the agents that run on it.\n\nRole : Lead AI Engineer - Agent Framework & Agentic Applications\n\nLocation : Chennai - Work from Office\n\nType : Full-time\n\nLevel : Lead Engineer\n\nTotal Experience : 8 - 12 years\n\nAbout the Role : \n\nBuild the Agent Framework : \n\n- Architect and build the framework - the orchestration engine, a model-agnostic multi-LLM layer with routing and fallback, memory and state management, and a standard tool/integration layer (including MCP).\n\n- Bake in the standard capabilities - guardrails and security, observability and evaluation, human-in-the-loop approvals, cost governance, and lifecycle/versioning - so every agent inherits them by default.\n\n- Create reusable building blocks - templates, SDKs, and a clean developer experience so new agents are a thin layer of business logic, not a bespoke rebuild.\n\n- Set the standards - patterns, guardrail policies, evaluation practices, and documentation that internal and client teams follow.\n\nDevelop Agents : \n\n- Design, build, and ship production agents on the framework for real business use cases.\n\n- Ground agents in knowledge (RAG) - retrieval over vector stores, context and prompt engineering, and integration with real systems (e.g., source control, ticketing, internal apps).\n\n- Evaluate and continuously improve - build eval datasets, automated scoring (including LLM-as-judge), and regression testing; use production traces to drive quality up.\n\n- Ship safely - versioning, staged/canary rollout, and rollback, with agents observable and cost-controlled in production.\n\nLead & Collaborate : \n\n- Provide technical leadership - mentor engineers, review designs and code, and grow agent-development capability across the team.\n\nWhat We're Looking For : \n\n- Experience : 8 - 12 years in software engineering, with recent hands-on experience building and shipping LLM / agent applications to production.\n\n- Machine learning : a solid grounding in ML fundamentals - model behavior, evaluation, and data. Enough to reason about LLM capabilities, limits, and fine-tuning trade-offs (applied ML/NLP or MLOps experience a strong plus).\n\n- Programming : Strong Python (TypeScript/Node a plus); solid software-engineering fundamentals, system design, and API design.\n\n- Agent frameworks : Hands-on with an agent-orchestration framework (e.g., LangGraph / LangChain, or equivalent) and LLM provider APIs (Anthropic Claude, OpenAI, and others), including open-weight models.\n\n- Grounding & RAG : Retrieval-augmented generation, vector databases (e.g., pgvector, Pinecone, Chroma), embeddings, and prompt and context engineering.\n\n- Observability & evals : Experience tracing and evaluating LLM apps (e.g., LangSmith, Langfuse, OpenTelemetry) and building evaluation/regression harnesses.\n\n- Safety & security : Understanding of LLM-app risks - prompt injection, data leakage, least-privilege tool access - and how to guard against them.\n\n- Platform : Cloud (AWS/GCP/Azure), containers, CI/CD, and building reliable, reusable services or SDKs.\n\n- Leadership & communication : Ability to set technical direction, mentor, and communicate clearly with both engineers and business stakeholders.\n\nNice to Have : \n\n- Experience with the Model Context Protocol (MCP) and building/integrating tool servers.\n\n- Multi-agent orchestration, agent memory systems, and cost-optimization (model routing, prompt caching).\n\n- Self-hosting or fine-tuning open-weight models; MLOps / LLMOps experience.\n\n- Client-facing or consulting background; ability to shape and demo solutions for prospects.\n\n- Domain exposure relevant to Ionixx's clients (e.g., fintech, healthcare) and open-source contributions.\n\nWhy Ionixx : \n\n- Own a high-visibility, strategic initiative from the ground up - real scope and real impact.\n\n- Work at the frontier of agentic AI, across internal products, demonstrations, and client delivery.\n\n- Shape the standards and reusable IP that define how Ionixx builds agents.\nSkills\nMachine Learning, Python, LangChain, RAG, Prompt Engineering, Artificial Intelligence, Agentic AI, LLM","description_format":"text","description_chars":4162,"description_truncated":false,"requirements":{"experience_years_min":8,"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":"2026-09-25T18:04:06Z"}],"liveness":{"score":45,"band":"ok","label":"Likely open","p_open":0.85,"p_active":0.702,"p_room":0.75,"age_days":22,"expected_fill_days":24,"reasons":["seen:22","velocity","win:late"],"computed_at":"2026-10-02T05:45:00Z"},"pay":{"stated_usd_annual":41928,"is_top_pay":false},"html_url":"https://alion.io/job/ionixx-technologies-lead-ai-engineer-agent-framework-agentic-applications","json_url":"https://alion.io/job/ionixx-technologies-lead-ai-engineer-agent-framework-agentic-applications.json","meta":{"generated_at":"2026-10-03T00:51:27Z","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":587,"day_limit":5000,"remaining_today":4413,"minute_limit":60,"resets_at":"2026-10-04T00:00:00Z"}}}