{"id":3917223,"url":"https://alion.io/job/accenture-technology-architect-30","title":"Technology 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":2120,"ghost_share":0.001,"stale_share":0.17,"repost_share":0.006,"time_to_fill_p50_days":5,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Backend","role_family":"Backend","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":["Mumbai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":true},{"name":"AWS","optional":true},{"name":"CI/CD","optional":true},{"name":"Draw.io","optional":true},{"name":"GCP","optional":true},{"name":"Git","optional":true},{"name":"JavaScript","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"LLM","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"LLMOps","optional":true},{"name":"Milvus","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"Nest.JS","optional":true},{"name":"Node JS","optional":true},{"name":"OpenSearch","optional":true},{"name":"OWASP","optional":true},{"name":"pgvector","optional":true},{"name":"Platform Engineering","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"Python","optional":true},{"name":"RAG","optional":true},{"name":"Rest API","optional":true},{"name":"Semantic Search","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-05T00:00:00Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-08T01:24:02Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Project Role : Technology ArchitectProject Role Description : Design and deliver technology architecture for a platform, product, or engagement. Define solutions to meet performance, capability, and scalability needs.\nMust have skills : Generative AI\nGood to have skills : Python (Programming Language)\nMinimum 5 year(s) of experience is required\nEducational Qualification : 15 years full time education\nSummary:\nWe are seeking an experienced Full Stack Engineering Tech Lead with strong expertise in Generative AI, Agentic AI frameworks, and modern cloud-native application architectures.\nThe role involves leading the design and development of enterprise-scale AI platforms, including RAG pipelines, agentic AI workflows, and microservices-based backend systems. The candidate will work closely with product owners, architects, and engineering teams to build scalable AI-driven applications deployed on cloud platforms like AWS or GCP.\nThe ideal candidate should combine deep hands-on engineering expertise with technical leadership, driving innovation and mentoring engineers while building production-grade AI systems.\nRole: Full Stack Engineering Tech Lead (GenAI / Agentic AI Platforms)\nRoles & Responsibilities:\nTechnical Leadership\nLead the design, architecture, and development of AI-driven full stack applications.\nProvide technical direction and best practices for implementing Generative AI and Agentic AI solutions.\nMentor and guide full stack engineers and AI engineers.\nConduct architecture reviews, code reviews, and technical design discussions.\nDrive engineering excellence, scalability, and security standards across AI applications.\nAI / GenAI Platform Development\nArchitect and implement enterprise RAG (Retrieval Augmented Generation) pipelines.\nDesign agentic AI workflows and orchestration pipelines using LangGraph.\nDevelop scalable LLM inferencing pipelines using open-source or enterprise LLMs.\nDesign document ingestion pipelines including chunking, embedding, vectorization, and retrieval workflows.\nEvaluate and experiment with emerging AI standards and technologies such as MCP (Model Context Protocol).\nDesign multi-agent orchestration frameworks for enterprise AI applications.\nBackend & Microservices Architecture\nDesign and develop scalable microservices architecture using NestJS and Python.\nDefine standards for REST API design, versioning, and secure API development.\nImplement event-driven integrations using webhooks and asynchronous communication patterns.\nDesign DAG-based workflows and orchestration pipelines for AI processing pipelines.\nData & AI Infrastructure\nArchitect vector database solutions for semantic search and AI retrieval systems using:\no pgVector\no OpenSearch\no Milvus\nDesign metadata and operational data storage architecture using PostgreSQL / AWS RDS.\nImplement distributed data processing pipelines using Apache Spark or equivalent frameworks.\nOptimize embedding storage, indexing, and retrieval performance.\nCloud & Platform Engineering\nArchitect and deploy AI applications on AWS or GCP cloud platforms.\nDesign cloud-native AI architectures leveraging containerized workloads and managed services.\nDefine scalability, reliability, and resilience strategies for AI platforms.\nCollaborate with DevOps teams to implement CI/CD pipelines for AI application deployments.\nSecurity & Compliance\nImplement secure coding practices for APIs and AI applications.\nEnsure compliance with OWASP API security standards.\nDesign secure AI pipelines ensuring data protection and access control.\nEstablish security guardrails for AI integrations and data pipelines.\nArchitecture & Design\nTranslate functional business requirements into technical architecture and system design.\nDesign RAG architecture, retrieval strategies, and agentic AI workflows.\nDevelop architecture diagrams, solution blueprints, and system documentation using draw.io.\nDefine design patterns for AI orchestration, microservices, and cloud-native deployments.\nProfessional & Technical Skills:\nAI & GenAI Technologies\nLangChain\nLangGraph\nRAG pipeline architecture\nAgentic AI orchestration\nLLM inferencing pipelines\nKnowledge of emerging AI protocols such as MCP\nProgramming Languages\nPython\nNestJS / Node.js\nDatabases\nVector Databases\npgVector\nOpenSearch\nMilvus\nMetadata Stores\nPostgreSQL\nAWS RDS\nAPIs & Integration\nREST API development\nWebhooks\nSecure API design\nOWASP API security practices\nData Processing\nDAG-based processing pipelines\nApache Spark or distributed data processing frameworks\nCloud Platforms\nAWS or GCP\nTools\ndraw.io\nGit-based development\nCI/CD tools\nDesired Skills\nExperience with LLMOps / MLOps practices\nKnowledge of prompt engineering and LLM evaluation\nExperience with semantic search and embedding optimization\nExposure to multi-agent AI architectures\nExperience building enterprise knowledge assistants or AI copilots\nMandatory Project Experience\nCandidate must have hands-on implementation experience in enterprise AI systems, including at least one of the following:\nRAG-based enterprise knowledge assistant\nLLM inferencing platform\nAgentic AI workflow using LangChain / LangGraph\nDocument ingestion and semantic search pipeline\nExperience may come from industry projects, research initiatives, or AI platform development programs.\nLeadership & Soft Skills\nStrong technical architecture skills\nAbility to mentor engineers and guide development teams\nHands on technical design and programming\nStrong problem-solving and analytical thinking\nExcellent communication and stakeholder management skills\nAbility to translate functional requirements into scalable technical architectures\nStrong innovation mindset and experimentation with emerging AI technologies\nWhat We Value\nWe value leaders who:\nDrive innovation in Generative AI and modern engineering practices\nEncourage experimentation and rapid prototyping\nBuild scalable and secure enterprise AI platforms\nFoster continuous learning and technical excellence within engineering teams\n6-10 Years of exp.\nAdditional Information:\n- The candidate should have minimum 5 years of experience in Generative AI.\n- This position is based at our Mumbai office.\n- A 15 years full time education is required.\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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