Full stack ai developer

We are seeking a skilled AI Engineer with strong experience in Azure DevOps to design, build, and deploy scalable AI solutions.

The ideal candidate will have hands-on expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, and modern AI orchestration frameworks such as LangChain and LangGraph, along with experience deploying AI workloads on Kubernetes.

Design, develop, and deploy end-to-end agentic AI applications

Build RAG pipelines including data ingestion, embedding, retrieval, and response generation

Integrate and optimize LLMs (Azure OpenAI, OpenAI, and open-source models)

Implement AI workflows using LangChain, LangGraph, or similar frameworks

Develop and manage CI/CD pipelines using Azure DevOps

Containerize and deploy AI applications using Docker and Kubernetes (AKS)

Implement LLMOps / MLOps best practices for versioning, monitoring, and scaling

Expose AI services via REST APIs and microservices

Ensure security, performance, cost optimization, and scalability of AI solutions

Collaborate with product, data, and engineering teams to translate business requirements into AI systems

Proven experience in AI / Machine Learning / Generative AI engineering

Strong hands-on expertise with LLMs and RAG-based systems

Proficiency in Python

Experience with Azure DevOps (Repos, Pipelines, CI/CD automation)

Hands-on experience with Kubernetes (AKS preferred)

Practical experience using LangChain and LangGraph

Experience with vector databases (Azure AI Search, Pinecone, FAISS, Weaviate, etc.)

Strong understanding of prompt engineering, embeddings, chunking strategies, and retrieval techniques

Experience with Docker, microservices, and cloud-native architectures

Good to Have

Exposure to model fine-tuning, LoRA, or custom LLM deployment

Knowledge of LLMOps tooling and observability

Familiarity with cloud security and identity management