Agentic AI Platform Architect & Product Lead

r3 Consultant

Hyderabad, Telangana, India

Employment Type: Full-Time

Experience: 10+ years of overall software engineering experience, including 3+ years of hands-on experience in AI/ML, LLM application development, Generative AI, platform architecture, solution architecture, or technical product development.

Role Overview

We are looking for an experienced Agentic AI Platform Architect & Product Lead to drive the development and evolution of the Fluid AIQ Platform and lead AI-powered application development for upcoming client projects.

The ideal candidate will have strong hands-on experience building production-ready applications using LLMs, AI agents, Retrieval-Augmented Generation (RAG), tool/function calling, workflow orchestration, and modern AI frameworks.

This role goes beyond traditional chatbot development, focusing on building intelligent agentic applications capable of reasoning, planning, interacting with enterprise systems, using tools, and operating within defined guardrails.

The position combines AI architecture, hands-on engineering, technical leadership, and product commercialization. You will help transform platform capabilities into modular commercial offerings that can be deployed independently and expanded based on client requirements.

Key Responsibilities

1. Agentic AI Architecture & Platform Development

Design scalable architectures for agentic AI applications, including single-agent and multi-agent systems.
Define agent orchestration, tool usage, memory, state management, and workflow patterns.
Establish reusable reference architectures, implementation guides, client onboarding playbooks, and engineering standards.
Evaluate AI technologies, models, frameworks, and infrastructure based on business and technical requirements.
Contribute to the evolution and architecture of the Fluid AIQ Platform.

2. AI Application Development

Build production-ready applications using AI agents, LLMs, RAG, and workflow automation.
Implement tool/function calling, planning and reasoning workflows, and human-in-the-loop processes.
Develop integrations with enterprise APIs, business applications, and external systems.
Implement MCP Server/Client integrations and autonomous or semi-autonomous workflows.
Build AI-powered decision-support solutions and reusable platform components.

3. LLM & Generative AI Engineering

Work with LLM providers and models, including OpenAI, Anthropic/Claude, Azure OpenAI, Google Gemini, and open-source or local models.
Implement prompt engineering, structured outputs, context management, function calling, and model fallback strategies.
Evaluate and benchmark models based on cost, performance, latency, privacy, and business use cases.
Ensure flexibility in model and framework selection without unnecessary platform dependency on a single provider.

4. Product Leadership & Commercialization

Take technical and product ownership of Fluid platform components and client AI programs.
Help package platform capabilities into independent, commercially viable modules.
Support the commercialization of reusable platform capabilities and technical IP.
Develop sales-enablement materials and implementation guidance.
Track and report platform health, adoption, and delivery metrics to leadership.

5. AI Safety, Reliability & Governance

Implement guardrails and validation mechanisms to reduce hallucinations, incorrect tool usage, unauthorized actions, and unsafe outputs.
Design human-approval workflows where required.
Build reliable agent workflows with error handling, retries, fallback mechanisms, and observability.
Support release management, environment management, service-level objectives, and production support models.
Address security, privacy, compliance, and responsible AI requirements.

6. Technical Leadership & Collaboration

Lead and mentor architects and engineers working on agentic AI solutions.
Collaborate with architecture, development, and cross-functional teams.
Evaluate emerging AI technologies and build proof of concepts (POCs).
Ensure solutions meet business requirements, quality standards, and delivery timelines.

Mandatory Technical Skills

Agentic AI & Generative AI

Strong understanding of Generative AI, LLMs, AI agents, and agentic AI architectures.
Hands-on experience with RAG, prompt engineering, embeddings, vector search, context management, and AI evaluation.
Experience with agent orchestration, tool/function calling, multi-agent systems, agent memory and state, and human-in-the-loop workflows.
Understanding of agent guardrails, reliability, and observability.

Programming & Application Development

Strong programming skills in at least one of the following: Python or Node.js/TypeScript.
Experience with REST APIs, microservices, authentication and authorization, asynchronous processing, event-driven architectures, and database integration.

AI Frameworks & SDKs

Hands-on experience with one or more of the following: LangChain, LangGraph, LlamaIndex, OpenAI SDK, Anthropic SDK, Claude Agents SDK, or equivalent agent SDKs.
Ability to evaluate and select frameworks based on solution requirements rather than relying on a single technology.

LLM Integration

Experience integrating multiple LLM providers, preferably OpenAI, Anthropic/Claude, Azure OpenAI, Google Gemini, or Ollama/open-source LLMs.

Data Engineering & RAG

Experience with PostgreSQL, vector databases, pgvector, Pinecone, Weaviate, Qdrant, or similar technologies.
Knowledge of embedding models, document processing, semantic search, and hybrid search.
Familiarity with knowledge graphs and ontology design, including Neo4j, RDF/OWL, or GraphRAG.
Understanding of multi-tenant data architecture.

Cloud Platforms

Strong experience with at least one cloud platform: Microsoft Azure, AWS, or Google Cloud.

Good-to-Have Skills

Model Context Protocol (MCP) integrations.
Claude Code, Codex, GitHub Copilot, Cursor, and other AI coding tools.
Ollama and open-source LLMs.
Multimodal AI, Voice AI, and AI workflow automation.
AI observability, evaluation platforms, and model evaluation.
Fine-tuning, AI security, prompt-injection protection, and PII/data protection.
Enterprise SaaS, CRM, and ERP integrations.
AI FinOps and FinOps Foundation practices.
Cloud marketplace listings, including Azure Marketplace and AWS Marketplace.
Product management experience and experience commercializing consulting IP as licensed software.
Experience replacing or complementing traditional RPA solutions with AI-agent-based approaches.

What We're Looking For

A hands-on technical leader who can translate business requirements into scalable agentic AI solutions.
Someone who can combine architecture, engineering, platform development, and product thinking.
A professional capable of taking AI capabilities from proof of concept to production-ready and commercially deployable solutions.
Strong communication, technical decision-making, stakeholder management, and mentoring skills.

Interested in building production-grade Agentic AI platforms and bringing AI-powered products to market? Apply now!

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