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IndiaNIC Infotech - AI Systems Architect - GRC Platform

Actively Reviewing

IndiaNIC Infotech Limited

Ahmedabad Full-Time 4–8 yrs exp Posted 2 months ago

Job Description

Description

AI Systems Architect - Multi-Agent & RAG Platforms

Role Overview

We are seeking an experienced AI Systems Architect to design and build an advanced, scalable AI platform leveraging customized Retrieval-Augmented Generation (RAG) and multi-agent (agentic swarm) architectures. The ideal candidate will lead the development of intelligent, modular AI agents capable of collaborative problem-solving across Governance, Risk, and Compliance (GRC) domains, with seamless integration into compliance platforms such as EasyCompliance.

Key Responsibilities

Develop and optimize customized RAG pipelines tailored for enterprise GRC use cases.
Build modular agent frameworks allowing dynamic addition of new skills, roles, and tools.
Architect memory-driven agent systems, including shared memory, long-term context retention, and vectorless or hybrid memory approaches.
Enable interoperability with multiple AI models (open-source and proprietary), ensuring flexibility in model selection and deployment.
Deploy and manage AI models across local, cloud, or hybrid environments with performance and cost optimization.
Integrate AI-generated outputs into compliance systems (e.g., EasyCompliance), including automated evidence generation and embedding.
Design orchestration layers for agent coordination, task routing, and workflow execution.
Ensure security, data governance, and auditability in AI workflows, especially for GRC-related outputs.
Collaborate with stakeholders to translate compliance requirements into AI-driven solutions.

Required Skills & Qualifications

Strong experience with LLMs, RAG architectures, and prompt engineering.
Hands-on experience building or working with multi-agent systems (e.g., LangGraph, CrewAI, AutoGen, Semantic Kernel, or custom frameworks).
Deep understanding of memory architectures in AI systems (vector databases, vectorless approaches, knowledge graphs, or hybrid memory systems).
Experience deploying and managing open-source and commercial models (e.g., LLaMA, Mistral, GPT, Claude).
Proficiency in Python and AI/ML frameworks (LangChain, Haystack, or similar).
Experience with orchestration, distributed systems, and API design.
Familiarity with embedding pipelines, retrieval systems, and document processing.
Knowledge of containerization and deployment tools (Docker, Kubernetes).

Preferred Qualifications

Experience with GRC platforms, compliance automation, or audit systems.
Understanding of knowledge graphs and structured reasoning systems.
Experience building tool-using agents (function calling, plugins, external integrations).
Familiarity with vector databases (FAISS, Pinecone, Weaviate) and alternatives.
Background in system architecture for enterprise-grade AI platforms.
Exposure to security, risk, and compliance frameworks (ISO, SOC2, NIST).

Key Deliverables

Fully functional multi-agent AI system with expandable roles and capabilities.
Production-ready RAG pipeline integrated with GRC workflows.
Memory-enabled agent ecosystem with shared and persistent context.
AI-powered compliance evidence generation integrated into EasyCompliance.
Scalable deployment architecture supporting multiple AI models.

Nice-to-Have Traits

Strong problem-solving mindset with a systems-thinking approach.
Ability to work in fast-evolving AI environments and evaluate new tools quickly.
Experience in building extensible AI platforms rather than single-use solutions.

(ref:hirist.tech)

Required Skills

Retrieval-Augmented Generation Machine Learning Compliance frameworks Adobe Illustrator Python AutoGen Mistral Docker Kubernetes FAISS Weaviate AI-powered