AI Solutions Architect (Agentic AI & GenAI)

Interactive Manpower Solutions; Greater Noida, Mumbai; Hybrid; INR 1,800,000 - 2,400,000; Full time

Job summary

Interactive Manpower Solutions is seeking an AI Solutions Architect to design, develop, and implement intelligent AI agents that automate business processes and support operations.

The candidate will work with LLMs, prompt engineering, agent orchestration and API integrations to deliver scalable, governed AI solutions across enterprise environments.

Qualifications

• Hands-on experience building AI/LLM powered applications and workflows.
• Ability to deploy AI agents/LLM apps into production environments.
• Strong understanding of prompt engineering and orchestration.
• Experience with API integrations and enterprise systems.
• Ability to translate business requirements into technical designs.
• Knowledge of responsible AI practices and governance.

Responsibilities

• Design, build, deploy and maintain production-grade AI agents and LLM-powered applications.
• Develop agent workflows and define behaviour, execution logic, and boundaries.
• Integrate AI agents with internal tools, APIs and enterprise systems.
• Translate business requirements into technical specifications and workflows.
• Identify automation opportunities to improve operational efficiency with Generative AI.
• Create and maintain technical documentation and SOPs.
• Collaborate with cross-functional teams to identify use cases and deliver AI solutions.

Skills

AI/LLM development

REST API integration

Technical writing

Analytical thinking

Communication

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

OpenAI APIs

Job description

Role: AI Solutions Architect (Agentic AI & GenAI Applications)

Location: Mumbai/Noida

Experience: 2-7 Years

Employment Type: Full Time, Permanent

Job Summary:

We are looking for an AI Solutions Architect to design, develop and implement intelligent AI agents that automate business processes and support real-world business operations.

The ideal candidate will have hands-on experience with Large Language Models (LLMs), prompt engineering, agent orchestration, API integrations and enterprise AI applications. You will work closely with AI Development, Operations and Client Services teams to understand business requirements and translate them into scalable, reliable and well-governed AI solutions.

This is a hands-on technical role offering the opportunity to shape the design and implementation of AI agent systems from the ground up.

This role focuses on building production-ready AI agents, multi-agent systems, LLM applications and enterprise AI automation solutions. Experience building production-ready AI solutions is strongly preferred over purely analytical or predictive modelling experience.

Key Responsibilities:

• Design, build, deploy and maintain production-grade AI agents, multi-agent systems and LLM-powered business applications.
• Develop agent workflows, define agent behaviour and establish clear rules, boundaries and execution logic.
• Integrate AI agents with APIs, internal tools, business applications and existing enterprise systems.
• Translate business and operational requirements into technical specifications, agent workflows and practical AI solutions.
• Identify opportunities to automate business processes and improve operational efficiency using Generative AI and agentic systems.
• Develop and optimise prompts, tool-calling mechanisms, workflows and multi-step agent interactions.
• Ensure AI agents operate reliably, securely and within defined governance and business rules.
• Troubleshoot agent performance issues, improve response quality and implement appropriate validation and error-handling mechanisms.
• Create and maintain technical documentation, Standard Operating Procedures (SOPs), implementation guides and reusable playbooks.
• Collaborate with cross-functional teams, including AI, Engineering, Operations and Client Services, to identify use cases and deliver AI solutions.
• Analyse existing platforms, systems and business processes to identify integration opportunities and potential challenges.
• Support continuous improvement of AI agent architecture, orchestration workflows and deployment practices.

Required Skills & Experience:

• 2+ years of hands-on experience building AI, Generative AI or LLM-powered applications, workflows or automation solutions.
• Hands-on experience deploying AI agents or LLM applications into production environments.
• Strong understanding of prompt engineering, LLM orchestration, AI agents and tool/function calling.
• Experience integrating AI applications with REST APIs, third-party tools and business systems.
• Ability to translate business requirements into technical designs, workflows and working solutions.
• Understanding of agent workflows, context management, error handling, validation and responsible AI practices.
• Experience creating technical documentation, SOPs, playbooks or implementation guides.
• Strong analytical thinking, problem-solving and system-design skills.
• Excellent communication skills, with the ability to engage technical and non-technical stakeholders.
• Ability to work in a fast-paced environment and manage evolving business requirements.

Preferred Skills:

• Experience with frameworks and tools such as LangChain, LangGraph, LlamaIndex, Semantic Kernel or similar LLM orchestration frameworks.
• Experience with multi-agent systems and AI workflow orchestration platforms.
• Experience building RAG-based applications and agentic workflows using enterprise data sources.
• Knowledge of Python and/or JavaScript/TypeScript.
• Experience with OpenAI APIs, Azure OpenAI or other LLM providers.
• Familiarity with function calling, structured outputs, RAG (Retrieval-Augmented Generation), vector databases and agent memory.
• Understanding of AI evaluation, guardrails, observability, monitoring and security controls.
• Experience with workflow automation platforms, enterprise applications or multi-agent systems.

Good to Have:

• Experience building and deploying LLM-powered applications or AI agents in commercial or production environments.
• Experience delivering AI solutions for real-world business use cases, beyond POCs, prototypes or academic projects.
• Exposure to enterprise AI deployments, including integration with existing business systems and operational workflows.