Job Description: Agentic AI Engineer (3-5 Years Experience)

Location: Kolkata, West Bengal
Experience: 3-5 Years
Employment Type: Full-Time

Job Summary
We are seeking a highly skilled Agentic AI Engineer to design, develop, and deploy next-generation AI solutions powered by Large Language Models (LLMs), Multi-Agent Systems, Retrieval-Augmented Generation (RAG), and enterprise-grade AI integrations. The ideal candidate will have hands-on experience building production-scale Agentic AI applications that automate complex workflows, orchestrate multiple AI agents, leverage organizational knowledge, and integrate with enterprise systems and databases. Experience with Azure AI ecosystem, LangChain/LangGraph, vector databases, and AI product development is highly preferred. The role involves collaborating with product, engineering, and business stakeholders to deliver intelligent automation solutions across domains such as enterprise operations, customer support, legal, HR, healthcare, and analytics.

Key Responsibilities
1. Design & Develop Agentic AI Solutions

- Build and deploy AI agents, multi-agent workflows, and autonomous reasoning systems using frameworks such as LangChain, LangGraph, and similar orchestration platforms.
- Develop RAG, GraphRAG, and HybridRAG architectures leveraging enterprise knowledge bases and vector search systems.
- Implement agent memory, tool usage, planning, reasoning, and orchestration capabilities for enterprise applications.
- Fine-tune and optimize LLM-driven workflows for performance, scalability, and accuracy.

2. Enterprise Integration & AI Product Engineering

- Integrate AI solutions with business applications, APIs, databases, DevOps platforms,



ticketing systems, CRM tools, logs, and cloud services.
- Develop custom agent tools and connectors to enable end-to-end business process automation.
- Collaborate with product managers and stakeholders to translate business requirements into production-ready AI solutions.
- Ensure solutions meet enterprise standards for reliability, governance, security, and auditability.

3. Model Optimization, Evaluation & Deployment

- Evaluate, benchmark, and optimize AI systems using multiple LLMs and model-routing strategies.
- Monitor model performance, latency, quality metrics, and cost efficiency.
- Deploy and manage AI applications on cloud platforms, ensuring scalability, observability, and operational excellence.
- Implement testing frameworks, security controls, guardrails, and AI governance practices for production environments.

Skills & Qualifications
Required Technical Skills

- 3-5 years of experience in AI/ML, Data Science, Generative AI, or AI Product Engineering.
- Strong expertise in Agentic AI, Multi-Agent Systems, AI orchestration, and autonomous workflow development.
- Hands-on experience with:
- LangChain
- LangGraph
- LangFlow
- RAG, GraphRAG, HybridRAG
- Agent Memory & Tool-Using Agents
- Supervisor Agents

- Experience working with Large Language Models such as:
- Azure OpenAI




- GPT-4o / GPT-5
- Open-source reasoning models (Qwen, Gemma, Llama, etc.)

- Proficiency in Python and API development.
- Knowledge of vector databases, embeddings, semantic search, and Azure AI Search/Vector Search.
- Experience with cloud platforms, preferably Microsoft Azure.
- Understanding of software engineering practices, CI/CD, source control, and DevOps workflows.
- Strong problem-solving and analytical skills.

Required Qualifications

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Analytics, Information Technology, or related discipline.
- Proven track record of delivering AI solutions from concept to production deployment.
- Strong communication and stakeholder management skills.
- Ability to work in a cross-functional and rapid-paced product environment.

Preferred Qualifications

- Experience building enterprise-scale AI products in domains such as Healthcare, Legal, HR, Energy, Operations, or Financial Services.
- Experience with LLM fine-tuning, prompt engineering, model evaluation, and AI governance frameworks.
- Familiarity with Databricks, Azure AI Services, Azure DevOps, Microsoft Dynamics, Jenkins, and enterprise API ecosystems.
- Experience implementing AI guardrails, explainability frameworks, bias monitoring, PII redaction, and compliance controls.
- Exposure to predictive analytics, anomaly detection, forecasting, or intelligent automation products.
- Prior experience contributing to AI product strategy, innovation initiatives, or AI solution architecture.

Confidential

Invariz | Confidential Business Communication

📌 Agentic AI Engineer (Kolkata)
🏢 Invariz
📍 Kolkata