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

Responsibilities

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

Requirements

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

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.