GenAI Engineers

Top Gen AI Jobs; Chennai District; On-site; INR 4,038,000 - 6,459,000; Full time

Job summary

xtagservices is hiring GenAI Engineers for multiple positions to build and deploy enterprise Generative AI solutions with strong hands-on implementation experience. The openings are onsite across Hyderabad, Chennai, Bangalore and Pune, offering an immediate opportunity to contribute to production-grade AI systems.

Ideal candidates have 5–11 years of GenAI experience, with hands-on work in LLMs, RAG, OpenAI, Vector databases, prompt engineering, fine-tuning and model deployment.

Qualifications

• 5–11 years of hands-on GenAI experience in building and deploying enterprise solutions.
• Strong experience with LLMs, RAG, model fine-tuning and deployment.
• Proficiency with AI frameworks and production-grade ML systems.

Responsibilities

• Develop GenAI solutions for enterprise use.
• Build RAG-based applications using LLMs and Vector DBs.
• Work with AI Agent frameworks and orchestration.
• Handle model fine-tuning, experimentation, deployment, and monitoring.
• Support scalable and secure enterprise GenAI solutions.

Skills

LLM

RAG

Gen AI

OpenAI

Gemini

Vector Database

Prompt Engineering

Fine-tuning

Machine Learning

BERT

LLaMA

Model Deployment

MLflow

TensorFlow

PyTorch

Job description

Description

Hiring GenAI Engineers for multiple positions. The role focuses on building and deploying enterprise Generative AI solutions with strong hands-on implementation experience.

Key Details

• Company: xtagservices
• Role: GenAI Engineers
• Locations: Hyderabad | Chennai | Bangalore | Pune
• Experience: 5-11 years
• Posted: 1 day ago
• Salary: $42.2K–67.5K/yr
• Contract: Full-time
• Work type: Onsite
• Open positions: 6
• Budget up to 4x Max

Skills Required

• LLM
• RAG
• Gen AI
• OpenAI
• Gemini
• Vector Database
• Prompt Engineering
• Fine-tuning
• Machine Learning
• BERT
• LLaMA
• Model Deployment
• MLflow
• TensorFlow
• PyTorch

Responsibilities

• Develop GenAI solutions
• Build RAG-based applications using LLMs and Vector DBs
• Work with AI Agent frameworks and orchestration
• Handle model fine-tuning, experimentation, deployment, and monitoring
• Support scalable and secure enterprise GenAI solutions

Experience

• 5–11 years
• Strong hands-on experience in GenAI
• Experience building and deploying GenAI solutions
• Experience with model fine-tuning, experimentation, deployment, and monitoring
• Strong understanding of production-grade AI/ML systems

Additional Responsibilities

• Open positions: 6
• Budget up to 4x Max

More Skills

AI Agent development, RAG Pipeline Development, Model Design, Monitoring, Docker, Kubernetes, LLM Integration, Scalable AI Deployment, AI Security, Compliance

Prepare for this role

• Recommended resources to build the skills for this position. Sponsored.
• Top 20 Vector Databases Questions (Quick)
• Zenaique
• A focused vector-database interview question set from Zenaique.
• Top 50 Vector Databases Interview Questions
• Zenaique
• Curated vector database questions covering Pinecone, Weaviate, Qdrant, and more.
• Top 50 Fine-tuning Interview QuestionsZenaique
• Curated LLM fine-tuning questions covering LoRA, PEFT, RLHF, and more.

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