Job
Description
GenAI Engineer
Experience: 3 to 12 years Location: Chennai/Bangalore/Hyderabad Details On Tech Stack Programming: Advanced Python (OOP, async), REST API frameworks (Flask, FastAPI) Cloud: Strong experience with Microsoft Azure (App Services, Azure Functions, Blob Storage, Cosmos DB preferred) GenAI/LLM Ecosystem: Familiarity with LangChain, LangGraph, or similar orchestration frameworks Experience building solutions with RAG design patterns and prompt tuning (CoT, ToT, FewShot) Understanding of vector databases (e-g, FAISS, Pinecone, Azure Cognitive Search) Embedding models like Sentence Transformers, CLIP/SIGLIP, or similar Performance Optimization: Hands-on experience scaling solutions for high payload volumes Token management and handling long-form data inputs Data Integration: Ability to work with semi-structured and structured data formats, schema mapping, and transformation Version Control & CI/CD: Git, Azure DevOps/GitHub Actions pipelines Nice To Have Requirements To The Candidate Practical experience deploying GenAI applications to production in enterprise settings Familiarity with AgentOps/MLOps pipelines Exposure to VLLMs or lightweight open-source LLMs for enterprise deployments Experience supporting post-go-live production systems or hypercare phases Qualifications Essential functions Programming: Advanced Python (OOP, async), REST API frameworks (Flask, FastAPI) Cloud: Strong experience with Microsoft Azure (App Services, Azure Functions, Blob Storage, Cosmos DB preferred) GenAI/LLM Ecosystem: Familiarity with LangChain, LangGraph, or similar orchestration frameworks Experience building solutions with RAG design patterns and prompt tuning (CoT, ToT, FewShot) Understanding of vector databases (e-g, FAISS, Pinecone, Azure Cognitive Search) Embedding models like Sentence Transformers, CLIP/SIGLIP, or similar Performance Optimization: Hands-on experience scaling solutions for high payload volumes Token management and handling long-form data inputs Data Integration: Ability to work with semi-structured and structured data formats, schema mapping, and transformation Version Control & CI/CD: Git, Azure DevOps/GitHub Actions pipelines Would be a plus Practical experience deploying GenAI applications to production in enterprise settings Familiarity with AgentOps/MLOps pipelines Exposure to VLLMs or lightweight open-source LLMs for enterprise deployments Experience supporting post-go-live production systems or hypercare phases We offer Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package medical insurance, sports Corporate social events Professional development opportunities Well-equipped office About Us Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India,