{"id":1224055,"url":"https://alion.io/job/infosys-ai-engineering-architect","title":"AI Engineering Architect","company":{"id":223,"name":"Infosys","domain":"infosys.com","url":"https://alion.io/company/infosys","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":75,"open_postings":165,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-09-27T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":46000,"max_usd":103000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":775},"experience_years_min":13,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Google ADK","optional":false},{"name":"Grafana","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenSearch","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Pinecone","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prometheus","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Vertex AI","optional":false},{"name":"Weaviate","optional":false},{"name":"Agile","optional":true},{"name":"Databricks","optional":true},{"name":"LLMOps","optional":true}],"status":"live","first_seen_at":"2026-06-30T10:17:35Z","employer_posted_date":"2026-09-25","last_verified_at":"2026-09-26T08:53:40Z","board_verified":true,"closed_at":null,"days_open":89,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":89},"description":"Responsibilities\nAI Architecture & Engineering\nDefine and own AI reference architectures for generative AI, agentic systems, and AI augmented applications\nArchitect scalable solutions using LLMs, multi agent systems, orchestration frameworks, and AI pipelines\nDesign AI platforms supporting model serving, prompt management, RAG, and workflow orchestration\nEstablish architectural standards for performance, scalability, reliability, and cost efficiency\nPlatform Engineering & Integration\nBuild reusable AI components for LLM integration, vector search, embeddings, and inference services\nEnable secure and scalable deployment using Kubernetes, serverless platforms, and CI/CD pipelines\nIntegrate AI capabilities into enterprise systems using APIs, SDKs, and event driven architectures\nCollaborate with QE teams to embed AI into test automation, test data generation, and intelligent validation\nEngineering Governance & Quality\nDefine architectural guardrails for model lifecycle, versioning, monitoring, and rollback\nEnsure adherence to non functional requirements including performance, observability, and fault tolerance\nLeverage observability tools to monitor model performance and drift\nReview designs and implementations for architectural compliance and code quality\nMentor engineers and architects on AI engineering best practices\nCore Platforms, Frameworks & Tooling\nLLM and foundation model platforms (e.g., AWS Bedrock, Azure OpenAI, Vertex AI)\nAgentic AI and orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen, Google ADK or equivalent)\nVector databases and search technologies (OpenSearch, Pinecone, FAISS, Weaviate)\nModel lifecycle and deployment tooling (Kubernetes, containers, serverless runtimes)\nCI/CD and MLOps tooling for AI pipelines (GitHub Actions, Azure DevOps, Jenkins)\nObservability and monitoring tooling for AI systems (OpenTelemetry, Prometheus, Grafana)\nClient Orientation & Leadership\nPartner with product and engineering teams to identify AI opportunities and shape roadmaps\nSupport client workshops, RFPs, and solution presentations\nMentor engineers on AI/ML/Gen AI best practices and emerging technologies\nTranslate complex AI concepts into business-friendly narratives.\nTechnical requirements\n13+ years of experience in software engineering with 3+ years in AI with strong architecture ownership\nProven experience designing and implementing enterprise-scale AI engineering or MLOps platforms\nStrong hands on experience with LLMs, prompt engineering, RAG, and agent frameworks\nProficiency in Python, AI frameworks, and cloud-native AI services\nExperience in Kubernetes, CI/CD, and secure deployment of AI models\nExperience integrating AI capabilities into enterprise scale systems\nGood to Have Skills\nExperience with multi agent orchestration and autonomous workflows\nKnowledge of model observability and monitoring tooling\nExposure to QE platforms, test automation frameworks, or AI assisted testing\nDomain experience in regulated industries such as BFSI, Healthcare, Telecom\nCloud and AI certifications\nPreferred skills\nTechnology->Agile Testing->Agile Testing - ALL,Technology->AI-AI Engineering->AI/ML Solution Architecture and Design,Technology->AI-AI Engineering->Databricks AI Engineering Services,Technology->AI-AI Engineering->LLMOps,Technology->AI-AI Engineering->MLOps,Technology->AI-AI Engineering->Model Optimization,Technology->AI-AI Engineering->Model Support,Technology->AI-Generative AI->Conversational AI Platform,Technology->AI-Generative AI->Generative AI - Basic->chains,Technology->AI-Generative AI->Generative AI for Data Analytics,Technology->AI-Generative AI->Prompt Engineering,Technology->Architecture->Architecture - ALL,Technology->Enterprise Architecture->Digital Architecture\nEducation\nBachelor of Engineering","description_format":"text","description_chars":3787,"description_truncated":false,"requirements":{"experience_years_min":13,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","IT Outsourcing & Dedicated Teams"],"lifecycle":[{"event":"open","at":"2026-09-25T13:04:21Z"}],"liveness":{"score":11,"band":"cold","label":"Long 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