{"id":2788240,"url":"https://alion.io/job/hcltech-senior-technical-lead-125","title":"Senior Technical Lead","company":{"id":225,"name":"HCLTech","domain":"hcltech.com","url":"https://alion.io/company/hcltech","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Backend","role_family":"Backend","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":["Noida, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":22000,"max_usd":50000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":57},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon Neptune","optional":false},{"name":"Anthropic","optional":false},{"name":"BigQuery","optional":false},{"name":"Chain-of-Thought","optional":false},{"name":"Dependency Injection","optional":false},{"name":"FastAPI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Gemini","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google Cloud Spanner","optional":false},{"name":"GraphRAG","optional":false},{"name":"Hallucination","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Hybrid Search","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LoRA","optional":false},{"name":"Neo4j","optional":false},{"name":"OpenAI","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prompt Caching","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Pydantic","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"QLoRA","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Tool Use","optional":false},{"name":"Vertex AI","optional":false},{"name":"Weaviate","optional":false},{"name":"PEFT","optional":true}],"status":"live","first_seen_at":"2026-10-17T17:14:06Z","employer_posted_date":"2026-10-17","last_verified_at":"2026-10-17T21:20:18Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Summary\nYou will be a core engineer on the AI intelligence layer of an enterprise-grade AI application. Your day-to-day work spans designing and building LLM-powered pipelines, agentic reasoning workflows, semantic retrieval systems, and knowledge graph integrations that serve real business users at scale. You write Python every day. You are responsible not just for building AI features but for ensuring they work reliably and measurably in production - not just in demos.\nKey Responsibilities\nDesign and build natural language to SQL (NL2SQL) pipelines - schema grounding techniques, few-shot prompt construction, SQL validation and sanitisation, guardrail enforcement, query explanation generation, and robust error recovery for malformed or ambiguous queries\n\nBuild and maintain LangGraph-based agentic workflows - state machine design for multi-step reasoning, tool-use orchestration, memory and context management, human-in-the-loop interruption patterns, and agent output validation\n\nImplement retrieval-augmented generation (RAG) and graph-enhanced RAG (GraphRAG) systems - chunking strategies, embedding model selection and evaluation, hybrid retrieval (dense + sparse), reranking, entity traversal over graph databases, and grounded answer synthesis\n\nDesign and maintain knowledge graph schemas for business domain semantics - node and relationship type definitions, traversal patterns, semantic similarity scoring, and integration with vector search for combined retrieval\n\nBuild and operate LLM evaluation pipelines - RAGAS metrics (faithfulness, answer relevance, context recall), LLM-as-judge patterns, custom domain-specific quality metrics, regression testing on prompt changes, and hallucination rate monitoring in production\n\nOptimise LLM API usage across Vertex AI and Gemini - prompt caching, model tiering (Flash vs Pro selection criteria), context compression, cost attribution per feature, quota management, and graceful fallback strategies\n\nImplement vector embedding pipelines end-to-end - document chunking, embedding generation (text-embedding-gecko or equivalent), index construction and maintenance in AlloyDB pgvector and Vertex AI Vector Search, and scheduled freshness updates as source data changes\n\nWrite clean, async FastAPI endpoints that expose AI capabilities to frontend and downstream services, with proper streaming support, error handling, and OpenAPI documentation\n\nSkill Requirements\nPython - 5+ years of production-grade engineering: async / await, Pydantic, type hints, modular package design, pytest, and clean separation of concerns; not just notebook scripting\n\nLangChain or LangGraph - production experience building chains, agents, or state machines that handle real-world edge cases and fail gracefully; demonstrable shipped systems, not tutorials\n\nLLM APIs - Vertex AI / Gemini, OpenAI, or Anthropic; deep practical understanding of context windows, token budgets, structured output enforcement (JSON schema, function calling), and cost optimisation strategies\n\nRAG architectures - chunking strategies, embedding model evaluation, retrieval quality measurement (precision, recall, MRR), reranking approaches, and hybrid search implementation\n\nSQL - fluent in complex query writing: joins, window functions, CTEs, subqueries; must be comfortable reading and writing BigQuery and PostgreSQL dialect SQL without assistance\n\nVector search - hands-on production experience with at least one: pgvector, Vertex AI Vector Search, Pinecone, Weaviate, or ChromaDB; including index configuration, ANN parameter tuning, and embedding dimension trade-offs\n\nPrompt engineering - systematic, evidence-based approach: few-shot design, chain-of-thought prompting, output structuring, negative example inclusion, prompt versioning, and iterative evaluation methodology\n\nOther Requirements\nGraphRAG or knowledge graph experience - Neo4j, Spanner Graph, or Amazon Neptune with GQL or Cypher; entity-relationship traversal for context-enriched retrieval\n\nNL2SQL specialisation - prior work on text-to-SQL systems, schema linking, value grounding, or SQL correctness evaluation benchmarks (Spider, BIRD)\n\nLLM fine-tuning - instruction tuning, LoRA or QLoRA on domain datasets; experience setting up fine-tuning pipelines and evaluating fine-tuned models against base models\n\nFastAPI production patterns - background tasks, lifespan event management, dependency injection, streaming responses with SSE, and middleware design\n\nGCP Vertex AI platform beyond inference - Vertex AI Pipelines, Model Registry, and Evaluation Service\n\nAny enterprise domain depth - retail analytics, financial services, healthcare, supply chain, or HR analytics; domain knowledge accelerates prompt design and evaluation","description_format":"text","description_chars":4733,"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":["IT Consulting & Digital Transformation","IT Outsourcing & Dedicated Teams","Systems Integrators"],"lifecycle":[{"event":"open","at":"2026-10-17T17:14:06Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":20,"reasons":["conf:1","win:early","comp:brand"],"computed_at":"2026-10-17T22:26:43Z"},"pay":null,"html_url":"https://alion.io/job/hcltech-senior-technical-lead-125","json_url":"https://alion.io/job/hcltech-senior-technical-lead-125.json","meta":{"generated_at":"2026-10-17T22:26:43Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":378,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":225},"rest":"https://alion.io/mcp/rest/get_company?id=225"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fhcltech-senior-technical-lead-125"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fhcltech-senior-technical-lead-125"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fhcltech-senior-technical-lead-125"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/hcltech-senior-technical-lead-125\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fhcltech-senior-technical-lead-125"}]}