{"id":4205826,"url":"https://alion.io/job/accenture-large-language-model-architect-33","title":"Large Language Model Architect","company":{"id":271,"name":"Accenture","domain":"accenture.com","url":"https://alion.io/company/accenture","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":100,"open_postings":2137,"ghost_share":0.001,"stale_share":0.182,"repost_share":0.007,"time_to_fill_p50_days":5,"computed_at":"2026-11-12T10:38:37Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"LLM","optional":false},{"name":"A/B Testing","optional":true},{"name":"Agile","optional":true},{"name":"AI Agents","optional":true},{"name":"Azure","optional":true},{"name":"CI/CD","optional":true},{"name":"Docker","optional":true},{"name":"Embeddings","optional":true},{"name":"FastAPI","optional":true},{"name":"Function Calling","optional":true},{"name":"Git","optional":true},{"name":"Haystack","optional":true},{"name":"Human-in-the-Loop","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"LlamaIndex","optional":true},{"name":"LLM Evaluation","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"Microsoft Defender for Cloud","optional":true},{"name":"Microsoft Entra ID","optional":true},{"name":"Microsoft Fabric","optional":true},{"name":"MLFlow","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"NLP","optional":true},{"name":"OpenAI","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"Python","optional":true},{"name":"RAG","optional":true},{"name":"Semantic Kernel","optional":true},{"name":"Synthetic Data","optional":true}],"status":"live","first_seen_at":"2026-11-11T00:00:00Z","employer_posted_date":"2026-11-11","last_verified_at":"2026-11-12T23:35:34Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Project Role : Large Language Model ArchitectProject Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.\nMust have skills : Large Language Models (LLMs)\nGood to have skills : Microsoft Azure Data Services\nMinimum 5 year(s) of experience is required\nEducational Qualification : 15 years full time education\nSummary:\nAI Powered Tech Talent\nRole Summary / Description\nEngineer role in AI LLM Technology Architecture for Level 8/9. Hands-on engineering role focused on designing, building, integrating, testing and operationalizing enterprise-grade LLM, GenAI and agentic AI components across active client engagements.\nOwn platform-specific engineering on Azure, translating high-level architecture into working, production-quality components for LLM-driven applications, RAG pipelines, multi-agent workflows and AI platform integrations.\nBring practical industry experience in banking, insurance, healthcare, public sector, retail or energy to identify domain data, process constraints, controls and adoption risks while designing GenAI solutions that are safe, scalable and relevant.\nOperate as a hands-on Level 9 technical lead or Level 8 engineering lead, contributing code, design decisions, reusable patterns and engineering documentation.\nKey Responsibilities\nDesign and build LLM application components including prompts, tools, agents, orchestration flows, memory/context handling, retrieval pipelines and evaluation harnesses.\nCreate Foundry-based agents with enterprise tools, knowledge and memory integrate Azure AI Search for RAG implement secure API/tool calls through API Management, Logic Apps and Functions instrument traces, evaluations, guardrails and policy controls for production agents.\nImplement data ingestion, parsing, chunking, enrichment, embeddings, vector search and retrieval workflows for structured and unstructured enterprise content.\nEngineer safety and control components including PII detection/redaction, prompt-injection defenses, content filters, guardrails, authentication, authorization, lineage and audit logging.\nCollaborate with architects, data engineers, product owners and security stakeholders to convert solution designs into tested, observable and maintainable software components.\nMaintain technical artifacts such as component designs, integration specifications, deployment runbooks, evaluation results and reusable engineering patterns.\nRequired Qualifications\nBachelor s degree in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology or a related engineering discipline.\nLevel 9: typically 5+ years of software/data/AI engineering experience, including 2+ years in cloud-native engineering and 1+ year in GenAI, LLM, NLP or agentic AI delivery.\nLevel 8: typically 7+ years of software/data/AI engineering experience, including 3+ years in cloud-native architecture/engineering and 1-2+ years in GenAI, LLM, NLP or agentic AI delivery.\nHands-on coding experience in Python and strong understanding of APIs, distributed systems, CI/CD, testing, observability and secure SDLC practices.\nExperience delivering AI/ML or data products in at least one industry domain such as banking, insurance, healthcare, public sector, retail or energy.\nRequired Skills/ Experience\nHands-on experience with Microsoft Foundry / Azure AI Foundry, Foundry Agent Service, Azure OpenAI models, Azure AI Search, Prompt Flow, Azure Functions, Logic Apps, API Management, Event Grid, Microsoft Fabric, Entra ID, Key Vault, Azure Monitor and Application Insights.\nStrong understanding of LLM application architecture patterns including RAG, function/tool calling, agent orchestration, model invocation, prompt engineering, embeddings, vector databases and evaluation metrics.\nAbility to implement traditional ML and GenAI components across ingestion, feature/data preparation, model integration, deployment, monitoring and continuous improvement.\nPractical knowledge of security, privacy, governance, performance, scalability, reliability and cost controls for production AI systems.\nExperience with Git-based development, automated testing, CI/CD pipelines, infrastructure-as-code and agile delivery in client-facing environments.\nGood to Have Skills\nAzure AI Engineer, Azure Solutions Architect or Azure Developer certification experience with Microsoft Fabric, Semantic Kernel, Prompt Flow, private networking, Defender for Cloud and enterprise Responsible AI governance.\nExposure to open-source frameworks such as LangChain, LangGraph, LlamaIndex, Haystack, MLflow, FastAPI, Docker and Kubernetes.\nExperience with Responsible AI, model risk management, synthetic data generation, human-in-the-loop review, A/B testing and GenAI cost optimization.\n15 years full time educationAbout Accenture\nAccenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services-creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us atwww.accenture.com\nEqual Employment Opportunity Statement\nWe believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, militaryveteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicablelaw. 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