Aurigo - AI Architect in Bangalore, भारत

Role : AI ArchitectLocation : Bengaluru, https://jobeax.com/link/zDc0YtaNmEkNX3mZ : 10 - 15 years (8+ years in AI/ML, 2 - 4 years in GenAI/LLM systems).Role : AI Architect (Architecture Ownership).About Aurigo : Aurigo is an AI-native capital program management platform trusted by over 300 customers managing more than $450 billion in capital programs across North https://jobeax.com/link/6w7xHmBzoFXQCuIY over 40,000 projects delivered, Aurigo helps organisations in transportation, water and utilities, healthcare, higher education, and government plan, build, and manage infrastructure with https://jobeax.com/link/eIzYeiIF9DgM8IWf as one of the Top 25 AI Companies of 2024 and a Great Place to Work for three consecutive years, we leverage artificial intelligence to create smarter, more connected https://jobeax.com/link/J8k4mPAdvL9Oqlmm Aurigo, we don't just build software - we help shape the future of https://jobeax.com/link/BnIbKM29T2nRMtlj Overview : We are hiring an AI Architect to lead the design and evolution of enterprise-grade AI platforms and GenAI systems at https://jobeax.com/link/qAYqbkLnnVqh7KFx is a high-impact, architecture-first role focused on solving real-world AI problems beyond POCs - owning system design, production maturity, evaluation frameworks, and https://jobeax.com/link/S5WZ4WVua9kdbO1b will define how AI systems are built, deployed, observed, and scaled across the https://jobeax.com/link/BlfzrR6vDTAYAy98 Responsibilities : 1. Architecture & System Design : - Define end-to-end architecture for LLM-powered platforms, copilots, and agent-based systems.- Design scalable RAG architectures (retrieval, grounding, response orchestration).- Architect multi-agent systems integrating enterprise tools, APIs, and workflows.2. GenAI Platform & Knowledge Systems : - Own the design of enterprise knowledge systems powered by LLMs and vector databases.- Implement advanced retrieval strategies (hybrid search, re-ranking, context optimization).- Design memory, context management, and reasoning pipelines for complex workflows.- Optimize systems for accuracy, latency, reliability, and cost at scale.3. Evaluation, Observability & Governance : - Define and implement evaluation frameworks for RAG systems, agents, and copilots.- Establish AI observability including traceability, monitoring, and feedback loops.- Build guardrails, hallucination mitigation, and responsible AI controls.4. Cloud, MLOps & Production Engineering : - Architect deployment pipelines on AWS (Bedrock, OpenAI, and equivalent services).- Design systems for scale, resilience, and high availability using microservices.- Ensure production readiness : monitoring, rollback strategies, and cost optimization.5. Technical Leadership & Strategy : - Act as the AI/GenAI technical authority across engineering teams.- Mentor engineers and guide teams on best practices, trade-offs, and design choices.- Drive AI roadmap, platform vision, and enterprise adoption https://jobeax.com/link/znvmlvLTOQQbyOD6 Qualifications : - 10 - 15 years of experience in software engineering, AI, or data platforms (8+ years in AI/ML, 2 - 4 years in GenAI/LLM systems).- Proven track record designing and deploying production-grade AI/ML systems at scale.- Hands-on ownership of GenAI / LLM-based systems in production https://jobeax.com/link/RJlrlMwwlgVOmeQM Technical Expertise : - RAG architectures (end-to-end : ingestion - retrieval - generation).- LLM orchestration, prompting strategies, and system design.- Vector databases and retrieval optimization.- Agent frameworks such as LangChain, CrewAI, AutoGen, or equivalent.- Evaluation frameworks and metrics for AI systems.- AI observability, monitoring, and performance tuning.- Cloud platforms (AWS/Azure) and container orchestration (Kubernetes).- Python / .Net and relevant ML/AI libraries and https://jobeax.com/link/HbJlMxBqnhd2vhNj to Have : - Experience building enterprise AI platforms (not just single applications).- Exposure to AI governance, compliance, and ethical AI frameworks.- Background spanning MLOps, platform engineering, or applied AI research.- Familiarity with fine-tuning, RLHF, or model customization techniques.- Experience collaborating with business functions such as Sales, HR, Finance, or https://jobeax.com/link/jnRgi6qvtLBoxxjV Metrics : - Production-grade AI systems achieving high accuracy, low latency, and controlled cost.- Well-defined evaluation and monitoring frameworks adopted across teams.- Reusable AI platform components deployed and leveraged by multiple engineering teams.- Scalable AI architecture handling enterprise-scale data volumes and workflows.- Measurable improvement in time-to-production for new AI https://jobeax.com/link/FiQsz9a44B3C3x3Z This Role Stands Out : - True architecture ownership - take AI systems to Production not only POC work.- Opportunity to define AI engineering standards and set the technical direction for the organization.- High-visibility role driving enterprise AI transformation journey in an organization that is recognized as one of the Top 25 AI Companies - AI is core to the product, not a side project. (ref:hirist.tech)