Agentic AI Architect

About Position:

We are seeking a highly experienced Agentic AI Architect with 10-15 years of industry experience to lead the design, architecture, and implementation of next-generation AI-driven solutions. The ideal candidate will possess deep expertise in Agentic AI frameworks, large language models (LLMs), autonomous AI systems, and cloud-native architectures. This role involves collaborating with business and technology stakeholders to define AI strategies, architect scalable intelligent agents, and deliver enterprise-grade AI solutions leveraging Vertex AI and modern cloud platforms.

• Role: Agentic AI Architect
• Location: Hyderabad & Bengaluru
• Experience: 10 to 15 Years
• Job Type: Full Time Employment

What You’ll Do:

• Study the current business process, including users, decisions, handoffs, systems, information sources, exceptions, delays, controls and failure points.
• Separate problems that need AI reasoning from those better solved through process correction, rules, search, analytics, workflow automation or conventional software.
• Define the target process and show exactly where an AI assistant or agent participates, where deterministic controls apply and where a person must review or approve.
• Convert business goals into measurable outcomes such as reduced handling time, improved first-time accuracy, fewer manual handoffs, faster information retrieval, lower rework or better control compliance.
• Establish the current KPI baseline, target improvement, measurement method, data source, reporting frequency and business owner before claiming value.
• Explain expected capabilities, limitations, uncertainty, failure modes, dependencies and residual risks in language understood by business and technology stakeholders.
• Design end-to-end architectures covering models, RAG, knowledge sources, agent orchestration, tools, APIs, state, memory, user channels, identity, permissions and human escalation.
• Define clear boundaries for agent autonomy, including which actions are read-only, which require confirmation and which must never be delegated to an agent.
• Design for secure data access, tenant separation, privacy, audit evidence, prompt-injection resistance, least-privilege tools and controlled handling of sensitive information.
• Define the evaluation strategy, including representative business scenarios, test datasets, acceptance thresholds, tool-action checks, safety tests and regression gates.
• Define production requirements for response time, availability, throughput, cost, logging, tracing, quality monitoring, incident handling, rollback and model or prompt changes.
• Select appropriate models, retrieval approaches and frameworks based on quality, security, latency, cost, portability and operating constraints rather than vendor preference.
• Demonstrate deep proficiency in at least one AI development stack while adapting designs to enterprise-developed platforms, standards and custom frameworks.
• Build or guide technical prototypes to test the highest-risk assumptions before committing to full implementation.
• Review solution designs, code, prompts, tool contracts, data flows, test evidence and production-readiness material produced by engineering teams.
• Create architecture diagrams, decision records, capability boundaries, risk assessments, cost models, delivery roadmaps and operating-model documentation.
• Provide technical direction to AI engineers, QA engineers, data engineers, application engineers, security specialists and operations teams.
• Track whether deployed solutions achieve the agreed KPIs and recommend tuning, redesign or retirement when the expected value is not being realized.

Expertise You’ll Bring:

• 10+ years in software, data, cloud or solution architecture, including substantial hands-on experience with production AI or LLM-based systems.
• Strong understanding of business-process analysis, value-stream mapping, decision points, control requirements and measurable outcome design.
• Deep technical knowledge of LLMs, prompting, structured generation, embeddings, vector and hybrid search, reranking, RAG, tool use, agent orchestration, state and memory.
• Demonstrable expertise in at least one production AI stack, such as Vertex AI and Gemini with ADK, LangChain/LangGraph, Semantic Kernel, LlamaIndex, or an equivalent platform.
• Ability to review Python code, APIs, data pipelines, retrieval logic, agent workflows, auto…