Artificial Intelligence Engineer
8 hours ago
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
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