Artificial Intelligence Engineer

Role & responsibilities

We are looking for a highly skilled AI Engineer with 2-5 years of experience and at least 2

years of experience in building and deploying AI solutions, with strong expertise in

Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG),

and traditional Machine Learning pipelines and passionate about building intelligent, LLM-

powered applications. In this role, youll design, develop, and deploy AI systems to enable

conversational intelligence, reasoning, and automation capabilities. The ideal candidate

should be comfortable working across structured and unstructured data, ML, and software

engineering layers, leveraging frameworks like LangChain, LangGraph, and Azure OpenAI

to build scalable, agentic AI applications.

Youll have the opportunity to be part of AI-driven change management, driving greater

impact through efficiency, cost savings, and innovation. If you enjoy experimenting with

model architectures, integrating APIs, and bringing AI solutions to life seamlessly, we’d love

to work with you.

Key Responsibilities

• Design, build, and optimize end-to-end AI systems leveraging both LLMs and

classical ML models.

• Develop GenAI-powered applications using frameworks such as LangChain,

LangGraph, LlamaIndex and agentic architectures for workflow automation.

• Implement RAG pipelines — including document chunking, vector database

integration, semantic search and hybrid search. Experience in RAG optimization

techniques (query rewriting, reranking, memory-augmented approaches).

• Engineer and refine prompts, system templates, and chains for performance,

consistency, and contextual reasoning.

• Work with Rest APIs, well-versed in API integration with any UI.
• Design and manage multi-agent orchestration systems that interact and collaborate

across tasks.

• Develop, evaluate, and deploy traditional ML models using Python, Pandas, NumPy,

Scikit-learn, and other libraries.

Work closely with data engineers to ensure data readiness, feature engineering, and

model lifecycle governance.

• Deploy models using Azure ML, Azure OpenAI, Cognitive Services, and other Azure

AI offerings.

• Collaborate with product, data, and engineering teams to deliver production-grade AI

solutions.

• Maintain strong documentation, experiment tracking, and best practices in version

control and well versed with DevOps lifecycles

• Work with dynamic, agile team in delivering impact and sustain the performance with

consistent outcome.

Required Technical Skills

• Programming: Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow,

Streamlit, FastAPI etc)

• Generative AI: RAG, prompt engineering, LangChain, LangGraph, vector databases

(Azure AI Search, FAISS, Chroma, Weaviate)

• LLMs: Experience working with multiple models (OpenAI GPT, Claude, Gemini,

Mistral, Llama, etc.)

• AI Agents: Knowledge of multi-agent systems, agentic orchestration, tool usage, and

reasoning loops

• Data Background: Strong SQL, data engineering, ETL, preparation, transformation,

and feature engineering skills

• Azure Ecosystem: GIT, Devops pipelines, Azure AI Services, Azure OpenAI,

Cognitive Search, Azure AI Foundry, and related services

• Machine Learning: Regression, classification, clustering, feature selection, model

evaluation

• APIs & Integration: REST APIs, FastAPI, Streamlit (optional), or similar frameworks

• Versioning & Deployment: Git, CI/CD, MLflow (preferred)

Preferred candidate profile