Lead AI Solutions Architect
AI Platform, Agents, RAG & Automation
Experience: 10+ Years
Department: AI / Engineering
Location: Hyderabad
Employment Type: Contract-to-Hire (C2H) – 1-year
Compensation: Based on experience
Role
Define and lead the architecture of an Enterprise AI Platform covering AI Agents, RAG, LLMs, workflows, process automation, and enterprise tool integration. Provide technical leadership while remaining hands-on with critical architecture and prototypes.Key Responsibilities
- Define AI platform architecture, standards, and technical roadmap.
- Design scalable AI Agent, Agentic AI, and multi-agent architectures.
- Define enterprise RAG and knowledge architecture.
- Design AI workflow and business process automation architecture.
- Define reusable connector, plugin, and tool architecture.
- Architect integrations with Microsoft 365, Outlook, Teams, SharePoint, Jira, Git, Slack, databases, and enterprise applications.
- Define LLM strategy covering cloud, private, and open-source models.
- Establish AI security, governance, access control, and compliance.
- Define AI evaluation, observability, monitoring, and auditability.
- Lead architecture reviews, POCs, technology selection, and mentor AI engineers.
Required Skills
- Architecture: Enterprise Architecture, Solution Architecture, Distributed Systems, Microservices, Event-Driven Architecture, Scalability, Security.
- AI/LLM: Generative AI, LLMs, RAG, AI Agents, Agentic AI, Function Calling, Tool Calling.
- Agents: Agent Orchestration, Multi-Agent Systems, Planning, Reasoning, Memory, Human-in-the-Loop.
- Frameworks: LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI.
- RAG/Data: Vector Databases, Embeddings, Semantic/Hybrid Search, Reranking, Knowledge Graphs.
- LLM Infrastructure: OpenAI, Azure OpenAI, Anthropic, Gemini, Open-Source LLMs, vLLM, llama.cpp, Ollama.
- Enterprise Integration: Microsoft Graph, Microsoft 365, Outlook, Teams, SharePoint, Jira, Git, Slack, REST APIs, OAuth2, Webhooks, MCP.
- Engineering: Python, APIs, Git, CI/CD, Docker, Kubernetes, Azure/AWS/GCP.
- Security/Governance: AI Security, Prompt Injection, Data Privacy, RBAC, Agent Security, Audit, Responsible AI.
- Experience: 10+ years software engineering/architecture with significant hands-on GenAI/LLM experience.
- Education: Bachelor’s/Master’s in Computer Science, Engineering, AI, Data Science, IT, or equivalent.
Ideal Candidate
- Hands-on AI Architect capable of defining LLMs + RAG + Agents + Workflows + Automation + Connectors + Tools + Security + Governance.
- Proven technical leader who can architect the platform and guide engineering teams to production.
Pay: ₹3,000,000.00 - ₹3,500,000.00 per year
Work Location: In person
