AI Architect

Luxoft; Gurugram District; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Luxoft is seeking an experienced Generative AI Architect to lead enterprise GenAI design, architecture, and platform adoption across the organization. You will define AI strategy, build scalable, secure GenAI platforms, and enable AI-powered products with business value.

You will collaborate with business, engineering, data science, and leadership to deliver solutions leveraging LLMs, Agentic AI, RAG, and MLOps. The role requires deep cloud-native and enterprise integration expertise.

Qualifications

• Experience designing enterprise GenAI architectures for production-scale deployments.
• Experience with LLMs, retrieval augmentation, and agentic AI patterns.
• Strong cross-functional leadership and stakeholder communication.

Responsibilities

• AI Strategy & Architecture:Define and drive the enterprise Generative AI architecture vision, standards, and technology roadmap.Design scalable, resilient, secure, and cost-optimized AI solutions leveraging LLMs, Agentic AI frameworks, multimodal models, and AI platforms.Establish reference architectures, reusable frameworks, and best practices for enterprise AI adoption.Lead architecture reviews and provide technical governance across AI initiatives.Evaluate emerging AI technologies, models, frameworks, and vendors to guide strategic investments.Generative AI Solution Design:Architect and oversee the implementation of enterprise-grade GenAI applications, including:Intelligent Assistants and ChatbotsEnterprise Search and Knowledge ManagementDocument Intelligence and SummarizationCode Generation and Developer Productivity SolutionsAgentic AI and Autonomous WorkflowsMultimodal AI Applications:Design advanced RAG architectures using vector databases, knowledge graphs, semantic search, and

Skills

GenAI architecture

LLMs

RAG

MLOps

Cloud platforms

Python

Java/Node.js

Prompt engineering

Vector databases

Security & governance

Tools

LangChain

LlamaIndex

HuggingFace

Semantic Kernel

AutoGen or similar agent frameworks

Job description

Project description

We are seeking an experienced and visionary Generative AI Architect to lead the design, architecture, and adoption of enterprise-scale Generative AI solutions. This role will be responsible for defining AI strategy, architecting scalable and secure GenAI platforms, and enabling the successful implementation of AI-powered products across the organization.You should possess deep expertise in Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), MLOps, cloud-native architectures, and enterprise integration patterns. The architect will work closely with business stakeholders, engineering teams, data scientists, and technology leadership to deliver transformative AI solutions that drive business value.

Responsibilities

• AI Strategy & Architecture:Define and drive the enterprise Generative AI architecture vision, standards, and technology roadmap.Design scalable, resilient, secure, and cost-optimized AI solutions leveraging LLMs, Agentic AI frameworks, multimodal models, and AI platforms.Establish reference architectures, reusable frameworks, and best practices for enterprise AI adoption.Lead architecture reviews and provide technical governance across AI initiatives.Evaluate emerging AI technologies, models, frameworks, and vendors to guide strategic investments.Generative AI Solution Design:Architect and oversee the implementation of enterprise-grade GenAI applications, including:Intelligent Assistants and ChatbotsEnterprise Search and Knowledge ManagementDocument Intelligence and SummarizationCode Generation and Developer Productivity SolutionsAgentic AI and Autonomous WorkflowsMultimodal AI Applications:Design advanced RAG architectures using vector databases, knowledge graphs, semantic search, and hybrid retrieval techniques.Architect prompt engineering frameworks, agent orchestration patterns, memory mechanisms, and contextual reasoning pipelines.Platform & Cloud Architecture:Design cloud-native AI platforms on AWS, Azure, and GCP.Define AI infrastructure requirements, including GPU utilization, model serving, inference optimization, and scaling strategies.Architect enterprise AI workbenches and reusable platform capabilities.Design secure API and microservices-based architectures for GenAI integration.Enable hybrid and multi-cloud AI deployment strategies.AI Engineering & MLOps:Define enterprise MLOps and LLMOps frameworks for model lifecycle management.Architect CI/CD pipelines for AI model training, validation, deployment, monitoring, and governance.Lead implementation of AI observability, model monitoring, drift detection, performance tracking, and operational excellence.Guide optimization strategies, including model quantization, distillation, caching, and inference acceleration.Security, Compliance & Responsible AIEstablish AI governance frameworks aligned with organizational and regulatory requirements.Define security controls for GenAI systems, including prompt injection protection, data privacy, model security, and access management.Ensure compliance with Responsible AI principles, security regulations, and enterprise governance standards.Conduct architecture risk assessments and recommend mitigation strategies.Stakeholder Leadership & Innovation:Partner with business executives and domain leaders to identify high-value AI transformation opportunities.Translate business requirements into scalable AI architecture solutions.Lead discovery workshops, architecture assessments, and client presentations.Mentor AI engineers, solution architects, and development teams.Drive innovation through PoCs, accelerators, reusable assets, and AI platform components.Documentation & Governance:Develop architecture blueprints, design standards, technical roadmaps, and implementation guidelines.Present architecture recommendations, business cases, and technical strategies to leadership and executive stakeholders.Support enterprise-wide AI adoption and change management initiatives.

SKILLS

Must have

• 12+ years of overall IT experience with 6+ years in AI/ML and 4+ years leading Generative AI architecture and solution design initiatives.Proven experience architecting large-scale enterprise AI and GenAI platforms from concept through production deployment.Experience leading technical teams and cross-functional enterprise programs.Generative AI ExpertiseDeep understanding of:Large Language Models (GPT, Claude, Gemini, LLaMA, Mistral)Transformer architecturesDiffusion modelsMultimodal AI systemsAgentic AI frameworksStrong experience with:Prompt EngineeringRAG architecturesFine-tuning and model customizationEmbedding modelsAI orchestration frameworksTechnology StackExpert-level proficiency in Python.Strong experience with Java and/or Node.jsHands-on experience with:LangChainLangGraphLlamaIndexHugging FaceSemantic KernelAutoGen or similar agent frameworksData & Retrieval TechnologiesExperience designing enterprise data architectures supporting AI workloadsExpertise with vector databases, including:PineconeWeaviateChromaFAISSAzure AI SearchStrong understanding of ETL, metadata management, knowledge management, and data pipelines.Cloud & Platform EngineeringStrong expertise in one or more cloud platforms:Microsoft AzureAWSGoogle Cloud PlatformHands-on experience with:Azure OpenAIVertex AIAmazon BedrockAzure AI FoundryAzure MLMLflowKubeflowArchitecture & Enterprise SkillsStrong expertise in:Distributed systems architectureMicroservicesAPI designEvent-driven architecturesEnterprise integration patternsSecurity and governance frameworksExperience defining architecture standards and technology roadmaps.Leadership & Communication:Excellent stakeholder management and executive communication skillsAbility to influence technical and business leadersStrong consulting, presentation, and problem-solving abilitiesExperience mentoring architects, engineers, and AI practitioners

Nice to have

N/A