{"id":3791309,"url":"https://alion.io/job/hcltech-ai-solution-architect-i-12","title":"AI Solution Architect I","company":{"id":225,"name":"HCLTech","domain":"hcltech.com","url":"https://alion.io/company/hcltech","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Solutions","role_family":"Solutions","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":["Noida, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":".NET","optional":false},{"name":"AI Agents","optional":false},{"name":"Angular","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"COBOL","optional":false},{"name":"Copilot","optional":false},{"name":"CrewAI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"FinOps","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Hallucination","optional":false},{"name":"Java","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":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Vertex AI","optional":false},{"name":"C#","optional":true},{"name":"JavaScript","optional":true},{"name":"PostgreSQL","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2026-11-05T06:45:07Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-06T10:43:51Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Job Summary\nEngagement-level architect who owns the technical solution for individual modernization workstreams. Translates legacy application analysis (often surfaced via AI Force AI Workbench) into target-state cloud-native architectures, working closely with client architects and the CN COE delivery team. Brings deep expertise in legacy estate assessment-spanning COBOL/mainframe, Java EE monoliths, .NET, and RPG applications-combined with the ability to design agentic AI pipelines and GenAI-native application architectures. This is the first true ‘architect’ rung and the entry point into the consulting solutioning track.\nKey Responsibilities\nApplication Discovery & Current-State Assessment\nLead application discovery and current-state assessments using GenAI-assisted code analysis and AI Force AI Workbench.\nAssess and classify legacy portfolios-COBOL/mainframe, Java EE monoliths, legacy .NET, RPG, and end-of-life frameworks-using AI-assisted portfolio intelligence tools.\nConduct business rule extraction from legacy codebases using GenAI tooling, preserving institutional knowledge before modernization.\nProduce comprehensive application profiles: dependency maps, data flow diagrams, complexity scoring, and technical debt assessments.\nTarget-State Architecture & Migration Planning\nAuthor target-state architectures (containers, serverless, managed services, event mesh) with clear migration patterns: rehost, replatform, refactor, rearchitect, replace, and retain.\nDesign target-state architectures for post-modernization GenAI-native applications, incorporating RAG pipelines, LLM integration layers, and agent orchestration frameworks.\nCo-author PRDs and BRDs alongside client product owners, using AI-generated artifacts as accelerators.\nDefine non-functional requirements: scalability, resilience, observability, security, and FinOps.\nPartner with Platform Engineers to ensure the target architecture is buildable on the chosen landing zone.\nPresent technical recommendations to client director-level stakeholders\n\nLegacy Application Modernization\nApply GenAI-assisted business rule extraction to preserve institutional knowledge from COBOL, RPG, and legacy Java systems before migration.\nDesign modernization journeys across the full spectrum: mainframe offload, COBOL-to-Java/cloud-native transpilation, monolith decomposition into microservices, and UI framework migration (e.g., Angular to React).\nLeverage composable Agentic AI platforms such as ATLAS and AI Force 2.0 to accelerate modernization from discovery to production.\nDefine rollback playbooks and cutover strategies for high-risk legacy system cutovers.\nChampion the AI Force Legacy Modernization Recipes for repeatable, scalable delivery patterns\n\nAgentic AI & GenAI Application Modernization\nDesign and deploy agentic AI pipelines for automated code analysis, dependency mapping, transformation planning, and validation-reducing manual discovery effort by 60-70%.\nArchitect GenAI-native applications using patterns such as Retrieval-Augmented Generation (RAG), multi-agent orchestration, tool/function calling, and LLM fine-tuning.\nConfigure and govern multi-provider LLM integrations (Azure OpenAI, Google Vertex AI, AWS Bedrock) with appropriate routing, cost, and latency controls.\nDefine guardrails, evaluation frameworks, and observability stacks for GenAI-powered applications in production.\nIntegrate LLM-based code generation, semantic diff, and automated test generation into CI/CD pipelines to accelerate modernization velocity.\nAssess and mitigate AI-specific risks: hallucination, prompt injection, data leakage, and model drift for production GenAI deployments.\n\nSDLC & DevOps Transformation\nIntegrate GenAI tooling across the full SDLC: requirements, design, code generation, testing, security scanning, and documentation.\nEstablish AI-augmented CI/CD pipelines that include automated regression, semantic diff, and migration validation gates\n\nDefine branching strategies, migration-as-code patterns, and rollback playbooks for high-risk legacy cutover events.\nSkill Requirements\nCore Experience\n6-9 years of software engineering and architecture experience, with at least 2 years in an architect role.\nDemonstrated success leading at least 2 application modernization or cloud migration engagements.\nDeep knowledge of at least one hyperscaler service catalog (AWS, Azure, or GCP).\nComfort facilitating client workshops and producing professional architecture documentation.\nLegacy Application Modernization\nHands-on experience assessing and modernizing legacy systems: COBOL/mainframe, Java EE monoliths, legacy .NET, or RPG applications.\nFamiliarity with AI-led modernization platforms such as AI Force 2.0, GitHub Copilot, Amazon CodeWhisperer, or equivalent tooling.\nAbility to perform or oversee business rule extraction from legacy codebases using GenAI-assisted analysis.\nExperience applying the 6R/7R migration strategies (rehost, replatform, refactor, rearchitect, replace, retire, retain) to enterprise legacy portfolios.\nAgentic AI & GenAI Application Architecture\nWorking understanding of GenAI patterns (RAG, agents, evaluation) and how they apply to SDLC acceleration and legacy modernization.\nProficiency with agentic AI frameworks-LangChain, LangGraph, AutoGen, CrewAI, or equivalent-and multi-agent orchestration patterns.\nStrong understanding of GenAI application patterns: prompt engineering, LLM integration, semantic search, function/tool calling, and structured output.\nAwareness of responsible AI principles: hallucination mitigation, bias detection, data privacy, and governance in GenAI deployments\n\nOther Requirements\nCertifications & Frameworks\nProfessional-level cloud certification (AWS SA Pro, Azure Solutions Architect Expert, GCP PCA).\nTOGAF or equivalent EA framework exposure.\nIndustry vertical depth: financial services, insurance, healthcare, or public sector\nAdvanced Modernization & AI Tooling\nExperience with composable Agentic AI modernization platforms (e.g., ATLAS, AI Force 2.0 AI Workbench).\nMulti-provider LLM configuration and governance: Azure OpenAI, Google Vertex AI, AWS Bedrock-including routing strategies, cost controls, and latency SLOs.\nDemonstrated GenAI business rule extraction from COBOL, RPG, or legacy Java codebases\nKnowledge of vector databases, embedding models, and semantic search architectures (e.g., Pinecone, Azure AI Search, pgvector).\nExperience building autonomous data engineering pipelines for legacy data modernization.\nGTM & Evangelism Contribution\nLeads technical solutioning on RFPs and proposals; contributes target-state diagrams and assumptions to SOWs.\nDevelops AI Force-based modernization POVs and demo storylines for client leadership engagements (e.g., COBOL business rule extraction demos, Agentic AI transformation workshops).\nContributes to CN COE knowledge base: reusable modernization recipes, GenAI architecture reference patterns, and best-practice playbooks.\nRepresents HCLTech at industry events and client briefings as a thought leader in AI-led legacy modernization and GenAI application 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