AI Architect

NeerInfo Solutions; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

NeerInfo Solutions is seeking an experienced AI Architect to lead architecture for enterprise GenAI and agentic AI systems. You will design single-agent and multi-agent architectures, orchestrate components, and ensure secure data exposure to AI agents through MCP integrations.

You will collaborate with data scientists and engineers, drive reusable skills and prompts, and evaluate LangGraph, LangChain, AutoGen and related frameworks while enforcing guardrails and governance.

Qualifications

• Experience designing LLM-powered applications and AI agents.
• Strong architecture knowledge and hands-on engineering experience.
• Proficiency in Python, FastAPI and LangChain.
• Familiarity with enterprise AI platforms and cloud services.
• Capability to design end-to-end GenAI architectures with guardrails.

Responsibilities

• Define end-to-end architecture for enterprise GenAI and agentic AI solutions.
• Design single-agent and multi-agent architectures including orchestration and handoffs.
• Create MCP integration architectures securely exposing data, APIs, tools to AI agents.
• Define reusable skills, tools, prompts, and agent capabilities.
• Evaluate frameworks like LangGraph, LangChain, AutoGen, Semantic Kernel.
• Establish controls for security, observability, governance and responsible AI.
• Own stages of AI development lifecycle and ensure end-to-end connections.
• Collaborate with data scientists and software engineers to align on requirements.
• Stay updated on generative AI research and share learnings with the team.
• Promote responsible AI practices and conduct code reviews.

Skills

Python programming

FastAPI

LangChain

Azure AI Services

OpenAI

LangGraph

AutoGen

Semantic Kernel

Model Context Protocol (MCP)

Retrieval-Augmented Generation (RAG)

Education

Master’s degree in Computer Science or Artificial Intelligence (or equivalent experience)

Tools

Python

FastAPI

LangChain

Azure AI Services

OpenAI

LangGraph

AutoGen

Semantic Kernel

MCP integration

RAG frameworks

Job description

Experience in core development, with strong architecture and engineering knowledge with hands‑on experience designing LLM-powered applications, AI agents, multi‑agent systems, agent orchestration, Model Context Protocol (MCP) integrations, reusable AI Skills, Managed Agents, and Retrieval-Augmented Generation (RAG) solutions.

Proficiency in Python, FastAPI, LangChain and working experience AI Cloud Services like Azure AI Services, OpenAI.

Define the end-to-end architecture for enterprise GenAI and Agentic AI solutions

Design single-agent and multi-agent architectures, including orchestration, routing, delegation, handoffs, collaboration, and human-in-the-loop patterns

Design Model Context Protocol (MCP) integration architectures that securely expose enterprise data, APIs, tools, and capabilities to AI agents.

Define reusable Skills, tools, prompts, and agent capabilities that can be shared across multiple agents and business use cases.

Design solutions using Managed Agents / hosted agents and enterprise AI platform

Evaluate and recommend frameworks such as LangGraph, LangChain, AutoGen, Semantic Kernel, or equivalent agent orchestration frameworks.

Establish architectural controls for guardrails, security, observability, logging, tracing, governance, auditability, and responsible AI

Take ownership of individual stages of the AI development lifecycle (data pre-processing, model training, evaluation, optimization, or deployment) and understand how they connect end to end.

Collaborate with data scientists, software engineers, and product managers to understand project requirements, and flag technical feasibility concerns early.

Stay curious about advancements in generative AI research and share learnings with the team.

Follow and promote responsible AI practices, with awareness of bias mitigation, fairness, and traceability.

Participate in code reviews, both receiving feedback and reviewing peers’ code, to help maintain quality standards.

Support POCs for new technologies, taking responsibility for defined parts of the work.

Comfortable working in a fast‑paced and agile environment.

Good collaboration and communication skills.

Preferred Skill and Experience

Master’s degree in computer science, Artificial Intelligence, or a related field (or equivalent experience).

Experience in Fine tuning Open-Source AI Models

Strong understanding of one or more Domain expertise and associated Industry standards

Industry-acclaimed External Certifications, if applicable

Active participation in Technology forums