Full stack ai developer
Skills
About This Role
Role Overview
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.
Key Responsibilities
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
Required Skills & Experience
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
with Azure OpenAI Service
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
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