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  "job_description": "Join HCLTech! Proudly recognized as a Certified Global Top Employer 2025.\n\nHCLTech is a global tech company with 224,000+ HCLTechies across 60 countries, offering digital, engineering, and cloud solutions. Serving major industries like Financial Services, Manufacturing, Healthcare, Telecom, and more, its 12-month revenue ending September 2024 was $13 billion.\n\nHCLTech France: +500 HCLTechies. Offices: Paris, Lyon and Toulouse.\n\nWe’re looking for a seasoned GenAI SME- L3 to lead solution discovery, design, and implementation of Generative AI capabilities across business workflows. You will act as the trusted advisor for stakeholders, drive production-grade deployments, and establish governance and performance baselines to deliver measurable business impact.\n\nThis role sits at the intersection of AI engineering, product, and business consulting, ideal for someone who can translate business problems into GenAI solutions, and take them from prototype → pilot → production.\n\nThis is a permanent and onsite role. Please NOTE, freelancers are not considered for this role.\n\nKey Responsibilities\n\nStrategy & Advisory\n• Partner with business leaders to identify high-value GenAI use cases (e.g., knowledge retrieval, summarization, agentic automation, copilots).\n• Perform feasibility assessments, define ROI, TCO, and risk; develop roadmaps with stage gates (POC → Pilot → Scale).\n• Create reference architectures and patterns for RAG, agents, prompt orchestration, and evaluation frameworks.\n\nSolution Design & Delivery\n• Lead end-to-end solution delivery using LLM stacks (Azure OpenAI / OpenAI, Google Vertex, Anthropic, etc.).\n• Architect RAG pipelines (chunking, embeddings, vector stores, retrieval optimization, reranking).\n• Implement prompt engineering and prompt orchestration (templates, tools, memory, guardrails).\n• Build agent workflows (task planning, tool-use, function calling, multi-agent collaboration).\n• Productionalize with CI/CD, observability (latency, token usage, hit-rate), and cost controls.\n\nData & Governance\n• Collaborate with data teams to prepare corpora and embeddings, metadata strategies, and quality standards.\n• Implement evaluation & metrics: relevance, faithfulness, toxicity, bias, hallucination rate, task success.\n• Ensure responsible AI compliance: privacy, security, IP, safety, provenance, and audit readiness.\n\nPlatform & Enablement\n• Contribute to or manage internal GenAI platform (APIs, templates, guardrails, evaluation harness).\n• Create playbooks, reusable components, and documentation; conduct enablement workshops for stakeholders.\n• Mentor L2/L1 engineers and analysts; review solutions and ensure best practices.\n\nJob Requirements\n• 7–12 years total experience, with 3+ years hands-on in GenAI/LLMs (production deployments preferred).\n• Strong experience and knoledge on;\n• RAG (document processing, embeddings, vector DBs like Azure AI Search, Pinecone, Weaviate, Qdrant).\n• Agentic frameworks (LangChain, LlamaIndex, Semantic Kernel, DSPy).\n• Evaluation & Safety (automatic evals, structured outputs, guardrails, content filters).\n• Hands-on with Azure OpenAI (preferred) and one additional LLM provider (OpenAI, Anthropic, Google).\n• Proficiency in Python; experience building APIs/microservices (FastAPI/Flask), CI/CD, and observability.\n• Experience deploying on Azure (Functions, App Service, AKS, Storage, Key Vault, Monitor), or equivalent cloud.\n• Strong prompt engineering and orchestration skills (function calling, tools, templates, system prompts).\n• Familiarity with document ingestion pipelines (PDF/HTML/Office), chunking strategies, and reranking.\n• Solid understanding of security & compliance: PII handling, data residency, RBAC, private networking, secrets.\n• Excellent stakeholder communication; able to translate business requirements into technical designs.\n• Fluent in French and English C1 level is mandatory.\n\nOther skills preferred/Good-to-Have\n• Experience with M365 Copilot/Graph connectors, SharePoint indexing, Teams integrations.\n• Knowledge of vector DB ops (indexing strategies, HNSW/IVF, recall vs. precision tuning).\n• Background in ML Ops or Data Engineering for AI products.\n• Exposure to evaluation datasets creation and human-in-the-loop review processes.\n• Basic knowledge of GenAI cost modeling and optimization (caching, prompt compression, distillation).\n\nReady for a new challenge? Join a friendly, multinational company offering endless career opportunities in a dynamic, multicultural environment.\n\nApply now and submit your CV in English!\n\nWhy become an HCLTechie?\n\nAt HCLTech, we offer diverse opportunities to learn, innovate, and fast-track your career. You'll work with global clients and industry-leading experts, gaining access to mentorship and rewarding growth paths. Our people-friendly work culture fosters flexibility, leadership, and personal and professional growth, giving you the freedom to explore, experiment, and thrive.\n\nWe believe in doing things differently, offering hands-on training and coaching, and celebrating the passion and commitment of our teams. Discover the benefits of joining HCLTech:\n• Comprehensive benefits package.\n• Global career opportunities and mobility.\n• Flexible work environment supporting work-life balance.\n• Exciting projects and upskilling opportunities to shape your role.\n• Total wellbeing focus: Beyond professional growth, you’ll be able to collaborate with like-\n\nminded colleagues to drive meaningful impact through initiatives like our CSR Council, Diversity Council, Women Connect, and many more.",
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  "job_posted_at_datetime_utc": "2026-02-23T00:00:00.000Z"
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