Job Title

Job DescriptionAI Architect / Principal AI SME – Enterprise & Industrial AI PlatformsLocation: India (Hyderabad / Bangalore)Experience: 15–20+ YearsBusiness Unit: Digital Engineering / Advanced TechnologyRole SummaryCyient is looking for a seasoned Data and AI Architect / Principal SME to lead the design and implementation of enterprise-scale Data and AI solutions. Experience in building and architecting Data and AI platforms/applications across various domains such as Aerospace, Energy, Mining, Manufacturing, Healthcare & MedTech, Utilities, and Transportation domains is an added advantage. This role demands hands-on architectural depth in either Azure or AWS or Both cloud platform with GenAI, LLMs, Agentic AI frameworks, distributed data platforms, Digital Twin ecosystems, and hybrid cloud deployments, combined with strategic technology leadership.The candidate will act as a Chief Architect-level technical authority, driving Data & AI platform and application vision, reusable accelerators, IP creation, and domain-led AI transformation initiatives.Core ResponsibilitiesData Platform & Lakehouse EngineeringDesign and govern modern data platforms:Architecture Components:Lakehouse architecture (Medallion architecture)Delta tables & ACID transactional layersMulti-tenant architecture with cost governanceData mesh or federated data architectureTechnologies:DatabricksApache Spark (batch & streaming)Delta Live TablesApache DruidDremioKubeflow pipelinesAirflow orchestrationData Engineering Capabilities:Schema evolution & versioningMetadata & lineage managementData quality frameworksDimensional modeling for analyticsStreaming ingestion (Kafka-based)Enterprise AI & Agentic Architecture• Architect enterprise-scale Agentic AI frameworks using:LangGraphModel Context Protocol (MCP)Multi-agent orchestration frameworksMemory-driven AI systems• Design and implement:RAG pipelines (Hybrid RAG, Graph-RAG)Embeddings pipeline (Open-source & enterprise models)Prompt orchestration & guardrailsFine-tuning pipelines (PEFT, LoRA, domain adaptation)• Build secure LLM deployments (On-prem / Air-gapped / Cloud-agnostic).• Define LLMOps lifecycle:Evaluation harnessHallucination detectionObservability (tracing, telemetry)Model governanceAdvanced AI/ML & Deep Learning• Architect ML systems using:TensorFlow, PyTorchScikit-Learn, XGBoostLSTM, CNN, Transformer modelsVision-Language Models (VLMs)• Time-series forecasting & anomaly detection for industrial telemetry.• Computer Vision pipelines:YOLO-based detectionSemantic segmentationObject tracking• Model compression & edge deployment (quantization, pruning).• Edge AI deployment on embedded hardware platforms.Cloud, DevOps & Infrastructure• Cloud-native AI architecture on:AzureAWS• Containerization:o Dockero Kubernetes (Helm, Operators)• Infrastructure as Code (Terraform exposure preferred)• CI/CD for ML pipelines• Secure DevSecOps integration• Hybrid & on-prem deployments with compliance constraints.Databases, Graph & Vector Systems• RDBMS: PostgreSQL• NoSQL: MongoDB• Graph Databases: Neo4j (Ontology & Knowledge Graph modeling)• Vector Databases:o Pinecone / FAISS / Milvus / Enterprise Vector DBs• Context modeling and semantic search frameworks.Architecture Governance & Innovation• Conduct architecture reviews and technical due diligence (M&A context).• Define reusable AI platform blueprints and accelerators.• Lead patentable innovations & IP creation.• Mentor architects and senior engineers.• Engage with CXOs for AI roadmap definition.Domain-Specific AI ApplicationsDrive AI programs across Cyient industry verticals:• Aerospace – Fuel analytics, predictive maintenance, digital twin simulation• Energy & Utilities – Smart grid analytics, leak detection, asset health• Oil & Gas – Production intelligence, APM• Semiconductor – Tool matching, fab analytics, defect classification• Manufacturing – Process optimization, time-series anomaly detection• Buildings – Smart HVAC optimization & control analytics• Transportation – Vision-based traffic & infrastructure analyticsRequired Experience• 15+ years in Data, AI, and Platform Engineering.• 5+ years in AI Architecture leadership role.• Proven delivery of enterprise-scale AI platforms.• Experience in industrial / engineering AI ecosystems.• Strong background in distributed systems and scalable data processing.Educational Background• B.Tech / BE in Computer Science or related field• M.Tech / MS in Data Science / AI (Preferred)What Makes This Role Strategic for CyientThis role anchors Cyient’s ambition to build:• Cloud-agnostic AI platforms• Industrial-grade Agentic AI systems• Digital Twin–driven engineering intelligence• Secure enterprise LLM deploymentsThe AI Architect will directly influence AI-led engineering transformation across global customers.