{"id":3729858,"url":"https://alion.io/job/wipro-principal-engineer-2","title":"Principal Engineer","company":{"id":224,"name":"Wipro","domain":"wipro.com","url":"https://alion.io/company/wipro","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"lead","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":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"API Gateway","optional":false},{"name":"Asyncio","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"Datadog","optional":false},{"name":"IAM","optional":false},{"name":"Kong","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Okta","optional":false},{"name":"OpenSearch","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Pinecone","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Redis","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"UML","optional":false},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true}],"status":"live","first_seen_at":"2026-11-04T07:29:59Z","employer_posted_date":"2026-11-04","last_verified_at":"2026-11-07T21:31:03Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com.Job Description\nAbout the AI Technology Innovation Centre\nWe are establishing a world class AI research center called “AI Technology Innovation Center” (TIC) in Bengaluru. The TIC will drive research in frontier AI technology with top AI talent and state-of-the-art infrastructure. The research breakthrough will lead to commercialization of next generation AI solutions. The AI TIC is being strategically designed to establish a globally recognized leader in AI research and development, driving innovation and setting industry benchmarks. The TIC aims to attract, nurture, and retain top-tier AI talent in India by fostering a dynamic, inclusive, and high-impact work environment that encourages continuous learning and breakthrough thinking.\nBy seamlessly integrating commercial agility with a pioneering scientific mindset, we will deliver scalable AI solutions that address real-world challenges while pushing the frontiers of technology. This ensures that our AI-TIC excels in cutting-edge research and translates discoveries into tangible business value, reinforcing our position as a hub for AI excellence.\nThe Role Mandate\nAs the Principal Engineer of AI TIC, you’ll own the end-to-end system architecture and design and delivery of production-grade agentic and Generative AI systems (on-premise/cloud). This is a highly hands-on role requiring deep architectural insight, coding proficiency, and an obsession with performance, scalability, and reliability. You’ll architect secure, cost-efficient AI platforms, guide developers through complex debugging and optimization, and ensure all systems are observable, governed, and production ready. You will create a reference platform and AI pipeline on which TIC research will get translated to real product.\n͏\nWhy This Role - What You Gain\nFounding-stage platform ownership\nDefine architecture, standards and SDKs that every Centre team will build on.\nDirect link to global products\nCarry frontier research into dependable, observable and secure deployed systems.\nThe hardest form of the problem\nEngineer memory, emotion control and self-learning under real compute and reliability constraints.\nTechnical leadership without leaving code\nMentor, review, debug and ship as a true principal engineer.\nThe Larger Impact\nDetermine whether empathic agents become dependable products rather than demonstrations.\nCreate a secure, modular and cost-efficient platform for multimodal, memory-enabled, tool-using agents.\nLead model adaptation, compression and optimisation for self-managed GPU environments.\nCreate reusable SDKs, connectors, CI/CD templates, evaluation harnesses and observability.\nSet the engineering standards that become the Centre’s technical reputation.\n͏\nKey Responsibilities:\n Architect Production AI Systems: Design robust overall architectures for agentic systems (planning, reasoning, tool-calling), GenAI/RAG pipelines, and evaluation workflows. Create detailed design documents including flow/UML/sequence diagrams and AWS deployment topologies. Additionally, ensure architectures support advanced LLM training and inference workflows, incorporating distributed strategies for scalability.\nOptimize for Cost & Performance: Model throughput, latency, concurrency, autoscaling, CPU/GPU sizing, and vector index performance to ensure scalable, efficient deployments. Include optimization for multi-node GPU clusters and distributed training efficiency to reduce compute overhead.\nLead Debugging & Stability Efforts: Conduct deep-dive debugging, fix critical defects, and resolve production incidents; pair-program with developers to improve code quality and performance. Apply MLOps-driven stability practices, leveraging configuration management and automated recovery for high availability.\n Standardize Agentic Frameworks: Build reference implementations using Semantic Kernel (preferred), LangGraph, AutoGen, or CrewAI with strong schema validation, grounding, and memory management.\nImplement Observability & Monitoring: Set up distributed tracing, metrics, and logging via OpenTelemetry and Datadog. Standardize dashboards, alerts, and incident response workflows.\nGovern Evaluation & Rollouts: Build test and evaluation frameworks-golden sets, A/B experiments, regression suites, and controlled rollouts-to ensure consistent quality across releases.\nEstablish Engineering Standards: Create reusable SDKs, connectors, CI/CD templates, and architecture review checklists to promote consistency across teams.\nCross-Functional Leadership: Collaborate with product, data, and SRE teams for capacity planning, DR strategies, and post-incident RCA reviews. Mentor engineers to strengthen design and reliability practices\nHow the Centre Works\nThe TIC follows a research-to-product operating model. Scientists and engineers work as one team across hypothesis formation, algorithm design, model development, evaluation, platform engineering and technology transfer. Every role combines technical depth with ownership, reproducibility, responsible AI and clear communication of outcomes.\n͏\nQualifications and Experience\nExperience and leadership\nEducation: Bachelor’s/Master’s from a top-tier institute (IIT/Tier-1) in Computer Science, AI, or related field.\n7-10 years in software/AI engineering, including 4+ years in GenAI application development and 2+ years architecting agentic AI systems.\nExpert in Python 3.11+ (asyncio, typing, packaging, profiling, pytest).\nHands-on experience with Semantic Kernel, LangGraph, AutoGen, or CrewAI or equivalent.\nProven delivery of GenAI/RAG systems on AWS Bedrock or equivalent vector-based platforms (OpenSearch Serverless, Pinecone, Redis).\nDeep understanding of AWS ecosystem: EKS, Bedrock, S3, SQS/SNS, RDS, ElastiCache, Secrets Manager, IAM/Okta, Kong API Gateway management and automated recovery for high availability.\nWhat Success Looks Like (18-24 Months)\nA hardened, observable agentic system and platform having custom models on on-premise infrastructure.\nReference implementations, SDKs and CI/CD templates become the Centre default.\nQuality, safety, latency and cost are measurable and continuously improved.\nResearch lands in production safely through a regular, governed release cadence.\nProduction problems are detected early and converted into systemic improvements.\n͏\nMandatory Skills: GenAI for Internet Software Products.Experience: 5-8 Years\n.Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. 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