Solutions Architect

Job Description: AI Solution Architect Location: Hyderabad Work Mode: Hyd 5 days Office Experience: 12+ years Job Summary We are seeking a highly experienced AI Architect / GenAI to design, develop, and scale enterprise-grade AI platforms and agentic solutions. The ideal candidate will possess deep expertise across Generative AI, AgentOps, cloud-native engineering, and AI platform strategy , with hands-on proficiency in LLMs, orchestration frameworks, and multi-cloud deployments . This role requires a strong technical leader who can architect and operationalize AI ecosystems aligned with enterprise governance, scalability, and compliance standards. Key Responsibilities Design and implement end-to-end AI architectures — spanning data ingestion, experimentation, model deployment, observability, and lifecycle management. Lead the development of Agentic AI systems with advanced features such as AgentOps, observability, shared memory, A2A communication, and context-sharing via MCP. Architect and operationalize enterprise AI marketplaces/registries for governed, self-service publishing and consumption of models, datasets, and agents. Build and manage horizontal AI services at scale — prompt/RAG APIs, vector & feature stores, guardrails, evaluation, and observability frameworks. Collaborate with data, cloud, and engineering teams to deliver multi-cloud AI platforms using AWS, Azure, and GCP (especially Vertex AI, Agentspace, ADK). Implement MLOps, AIOps, and DevSecOps best practices for AI and agent lifecycle deployment, security, and monitoring. Develop AI blueprints covering retrieval pipelines, tool use, safety, zero-trust access, and multi-tenant isolation. Drive transition from traditional AI → GenAI → Agentic architectures , supporting LLM fine-tuning, RAG workflows, and autonomous agents. Define and enforce AI governance, ethical AI, and data compliance frameworks aligned with enterprise policies. Lead cross-functional teams, ensuring SDLC and Agile process alignment, while mentoring engineers and data scientists. Partner with leadership to shape AI platform strategy, integration roadmaps , and enterprise-wide adoption frameworks. Required Skills & Abilities Programming & AI Frameworks Proficiency in Python , Java , C# , or R . Hands-on experience with Generative AI frameworks : TensorFlow, PyTorch, LangChain, OpenAI Codex, Claude, Gemini, HuggingFace. Strong understanding of ML/DL paradigms — supervised, unsupervised, and reinforcement learning. Agentic AI & Autonomous Systems Experience with AgentOps , Agent Observability , and Agent Lifecycle Management . Knowledge of MCP (Model Context Protocol) for context sharing and A2A (Agent-to-Agent) communication. Familiarity with Shared Memory architectures and Agentic Workflow Orchestration . Ability to design and evaluate deterministic vs autonomous agentic architectures. Cloud & Platform Engineering Deep proficiency in AWS, Azure, and GCP (especially Vertex AI, Agentspace, and ADK ). Expertise in Infrastructure as Code (IaC) using Terraform, GitOps, Kubernetes. Strong grounding in SRE practices , including SLOs and error budgets. Experience integrating AI observability and policy enforcement gateways . MLOps, AIOps & DevSecOps Practical experience implementing CI/CD pipelines , model monitoring , governance , and versioning . Skilled in AIOps for automated performance monitoring and DevSecOps for secure AI lifecycle management. AI Architecture & Enterprise Integration Proven experience architecting AI Platforms , registries , and shared services with lifecycle metadata and chargeback models. Strong understanding of data mesh , policy-driven AI gateways , and multi-region resiliency . Knowledge of safety pipelines , evaluation harnesses , and guardrail frameworks for LLMs and agents. Ethical & Responsible AI Deep understanding of data governance , privacy , and ethical AI principles . Experience implementing responsible AI frameworks ensuring transparency and compliance. Leadership & Collaboration Strong leadership , mentoring , and stakeholder engagement abilities. Excellent communication skills with cross-functional and executive teams. Proven ability to work in agile environments aligned with SDLC standards.