AI Architect

Seeking an AI Architect – Agentic Platforms to define the architectural foundations that power company’s enterprise agent ecosystem. This role is responsible for designing and governing the architecture for agent-based integrations, agent registries, scoring/evals infrastructure, grounding patterns, and multi-agent orchestration platforms. The AI Architect provides deep technical leadership across engineering, product, data science, security, and cloud teams to ensure that agents are built safely, consistently, and with enterprise-grade reliability, performance, and observability. This role combines expertise in large-scale AI systems, distributed cloud architecture, and modern agentic frameworks.About the Roleexperience in cloud and distributed systems architecture focused on scalability, reliability, observability, and performance.designing enterprise AI/ML systems; 1+ years hands-on with GenAI, agentic workflows, RAG, LLM-based integrations, or multi-agent systems.Strong expertise with agentic frameworks and tooling (MCP, LangChain, LangGraph,LlamaIndex, autogen, crewai, Agent sdk,OpenAI SDK etc).Hands-on experience in modern software development and engineering practices.Proven experience integrating APIs and enterprise systems into agentic platforms and workflows.Ability to rapidly build AI-driven prototypes, proofs of concept, and demo-ready product experiences.Experience defining and governing enterprise architecture standards, patterns, and reference architectures.Deep understanding of MCP servers, tool calling, registries, eval pipelines, agent observability, and multi-agent orchestration.Hands-on experience with Azure and GCP, including Kubernetes, containerization, identity, networking, CI/CD, and API platforms.Familiarity with AIOps/MLOps stacks (MLflow, model registries, vector DBs, semantic layers, feature stores, monitoring).Strong knowledge of security, compliance, risk, and Responsible AI (RAI) considerations for enterprise agent systems.Demonstrated ability to partner across engineering, data science, product, and security teams to deliver complex AI platform architectures.ResponsibilitiesAI Agentic Platform Technical LeadershipDefine and evolve the enterprise reference architecture for AI agents, including orchestration frameworks, tool integration patterns, MCP servers, registries, and multi-agent coordinationDesign large-scale agent orchestration platforms that enable autonomous workflows across commerce, operations, and internal productivity domainsResponsible for operational uptime adhering to SLAs, planning upgrades, rolling out new capabilities and integrations for agent platform.Establish grounding patterns using semantic layers, vector search, knowledge models, and Retrieval-Augmented Generation (RAG)Architect and develop systems that connect agents to trusted enterprise data, APIs, and business servicesDevelop architectural patterns for safe, governed agent execution aligned with Responsible AI principlesEnterprise Platform Engineering ExcellenceArchitect scalable, fault-tolerant AI agent platforms across hybrid cloud environments (Azure & GCP)Establish architecture standards ensuring low latency, high availability, resiliency, and observability.Partner with cloud and platform engineering teams to deliver containerized, API-driven, secure infrastructure for agent workloadsDefine platform lifecycle patterns including versioning, release gating, rollback strategies, and performance benchmarkingEnable cost-efficient scaling of AI workloads across millions of enterprise and customer interactionsAgent Quality, Safety & Evaluation InnovationDefine, develop and operationalize the Agentic SDLC, including evaluation frameworks, safety testing, regression gates, and release readiness criteriaArchitect systems for continuous agent improvement using automated evaluation pipelines and human feedback loopsEstablish enterprise standards for hallucination mitigation, prompt safety, PII protection, and AI misuse preventionLead observability and AIOps patterns for agent monitoring, anomaly detection, and operational intelligenceDefine performance scoring frameworks for agent quality, reliability, and cost optimizationStrategic AI Platform InnovationPartner with engineering, product, and data science leaders to deliver intelligent agent platforms serving customer and enterprise use casesDrive innovation in multi-agent systems, LLM-powered workflows, and AI orchestration technologiesEvaluate emerging agent frameworks, tooling, and open standards to guide platform strategy and build-vs-buy decisionsContribute to platform engineering excellence by building reusable AI infrastructure and developer enablement capabilitiesProvide architectural mentorship and technical guidance across teams on agentic AI design, scalable engineering practices, and enterprise AI standards