AI Engineer – Azure AI Foundry
- LocationBengaluru
- Work typeHybrid
- EmploymentFull-time
- Posted3 November 2026
- SourceAvanade's careers page (Workday)
Live checkFirst seen 8 days ago; still listed on Avanade's careers page 1 h ago.
Posted beforeRoleFinder first saw this role on 8 October 2026, 21 days before this listing. Reposts are often real openings that took long to fill.
At a glance
- Experience4 to 6 years
- EducationBachelor's degree
- Skills and toolsAzure, NLP, FastAPI, Flask, Python, scikit-learn, PyTorch, TensorFlow
Read from the ad by RoleFinder rules; the description is the source.
Back from the application? Add your CV and RoleFinder scores your fit for this role, then ranks your best 12 open roles where you want to work, each with a one-line reason.
Check my fitAbout the role
AI Engineer – Azure AI Foundry
Experience
4 – 6 years
Level
Mid-Level
Location
Delhi / Mumbai / Bangalore (India)
Employment Type
Full-time
Primary Skills
Azure AI Foundry, RAG, AI Agents, AI / ML
Role Summary
We are looking for an AI Engineer with hands-on experience in building Generative AI solutions on Microsoft Azure. You will design and develop Retrieval-Augmented Generation (RAG) pipelines and AI agents using Azure AI Foundry, working within a team under the guidance of senior engineers and architects, and contribute to production-grade AI/ML solutions for enterprise clients.
Key Responsibilities
- Develop and deploy RAG-based applications using Azure AI Foundry, Azure OpenAI, and Azure AI Search.
- Build AI agents using Azure AI Foundry Agent Service, including tool/function calling and basic multi-step workflows.
- Implement document ingestion pipelines: parsing, chunking, embedding generation, and vector indexing.
- Write and iterate on prompts; apply prompt engineering techniques to improve answer quality and reduce hallucinations.
- Build, train, and evaluate classical ML / deep learning models for classification, forecasting, NLP, or similar use cases.
- Expose AI capabilities through REST APIs (FastAPI / Flask) and integrate them with front-end and enterprise systems.
- Run evaluation of RAG and agent outputs (groundedness, relevance, accuracy) using Azure AI Foundry evaluation tools.
- Write clean, tested, well-documented code and participate in code reviews.
- Collaborate with product owners, data engineers, and QA teams to deliver sprint commitments.
Required Skills & Experience
- 4 – 6 years of total experience in software / data / AI engineering, with at least 1.5 – 2 years in Generative AI.
- Hands-on experience with Azure AI Foundry (model catalog, deployments, prompt flow, evaluations).
- Practical experience building RAG solutions end to end (embeddings, chunking, vector search, retrieval, re-ranking basics).
- Experience building AI agents using Azure AI Foundry (Agent Service) or frameworks such as Semantic Kernel, LangChain, or AutoGen.
- Strong Python programming skills; good understanding of REST APIs and JSON.
- Working knowledge of AI/ML fundamentals: supervised / unsupervised learning, model evaluation, feature engineering, scikit-learn, and PyTorch or TensorFlow.
- Familiarity with Azure services: Azure OpenAI, Azure AI Search, Blob Storage, Azure Functions, Key Vault.
- Working knowledge of Git and CI/CD basics.
.
Good to Have
- Azure certifications (AI-102, DP-100, or AZ-204).
- Exposure to Azure Machine Learning, Azure Databricks, or Microsoft Fabric.
- Experience with Docker and basic Kubernetes / Azure Container Apps.
- Exposure to responsible AI practices and content safety.
Soft Skills
- Good written and verbal communication; able to explain technical work to non-technical stakeholders.
- Ownership mindset, eagerness to learn fast-evolving AI tooling.
Education
B.E. / B.Tech / M.E. / M.Tech / MCA / M.Sc in Computer Science, Data Science, AI/ML, or a related field.
.
Get open roles ranked against your CV
Add your CV once. RoleFinder ranks the open roles where you want to work, plus remote ones, against it, shows your best 12 with a one-line reason each, and emails you new matches once a week. The file is read once by AI and not kept; employers never see it.
Sign in with Google or email to start. How we handle your CV