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Salary
≈ $30k – $71k per year (Estimated)
Location
In office (Pune, Bengaluru, Bhopal)
Seniority
Staff

First seen by Alion on Aug 26, 2026.

Overview
Company
Impact
Profile match
Transform your business with cutting-edge staffing solutions. We connect exceptional talent with outstanding opportunities, driving growth and innovation. Fast hiring, precision match, quality assured professionals.

Role Overview :

We are looking for an experienced AI Architect Agentic AI & LLM Platforms to design, architect, and implement enterprise-grade AI solutions using Generative AI, Large Language Models (LLMs), Agentic AI, and Multi-Agent Systems.

The ideal candidate will have strong expertise in AI/ML architecture, LLM platforms, agent orchestration, RAG, cloud technologies, and enterprise integration. The role requires a hands-on architect who can translate business requirements into scalable, secure, and production-ready AI solutions.

Key Responsibilities :

- Define end-to-end architecture for Agentic AI and LLM-based platforms.

- Design autonomous AI agents capable of reasoning, planning, memory management, tool usage, and task execution.

- Architect multi-agent systems and agent orchestration workflows.

- Design and implement RAG (Retrieval-Augmented Generation) solutions, embeddings, vector search, and knowledge retrieval pipelines.

- Evaluate and integrate LLMs such as GPT, Claude, Gemini, Llama, Mistral, and other foundation models.

- Work with frameworks such as LangChain, LangGraph, AutoGen, Semantic Kernel, CrewAI, or equivalent.

- Design scalable AI platforms on Azure, AWS, or GCP.

- Integrate AI agents with enterprise applications, APIs, databases, microservices, and event-driven systems.

- Define strategies for prompt engineering, context management, memory, grounding, evaluation, and guardrails.

- Architect AI solutions for performance, scalability, reliability, security, latency, and cost optimization.

- Establish LLMOps/MLOps practices including CI/CD, monitoring, model evaluation, observability, and deployment.

- Ensure Responsible AI, security, privacy, governance, and compliance requirements are incorporated into AI architecture.

- Create reusable AI accelerators, reference architectures, design patterns, and technical standards.

- Work closely with business stakeholders, engineering teams, data scientists, and technology leadership.

- Mentor engineering teams and provide technical leadership on complex AI initiatives.

Tech Stack :

- Agentic AI, LLMs, Generative AI, RAG, Vector Databases, Python, FastAPI, Microservices, Docker, Kubernetes.

Skills

Artificial Intelligence, Agentic AI, LLM, Generative AI, RAG, LangChain, LangGraph, AWS, MLOps, Python, AI Architecture

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