AI/ML Engineer (Generative AI & LLMs)

Role Overview

We are seeking a highly skilled AI/ML Engineer with strong expertise in Generative AI and Large Language Models (LLMs). The ideal candidate will have a solid foundation in machine learning, data science, and AI fundamentals, along with hands-on experience in designing, building, and deploying scalable GenAI solutions in enterprise environments.

Key Responsibilities

Core AI/ML & GenAI Development

• Design and develop advanced AI/ML models with a focus on Generative AI use cases
• Build and implement scalable LLM-powered applications for enterprise solutions
• Apply strong fundamentals in NLP, neural networks, and statistical modeling
• Develop, optimize, and deploy Retrieval-Augmented Generation (RAG) pipelines

LLM & Generative AI Expertise

• Work extensively with leading LLMs such as OpenAI, Google (Gemini), Anthropic (Claude), Mistral, and LLaMA
• Build, fine-tune, and deploy LLM-based applications using platforms like Vertex AI and Hugging Face
• Develop advanced prompt engineering strategies, reusable prompt templates, and prompt tuning techniques
• Implement agentic frameworks for complex AI-driven workflows
• Apply guardrails and evaluation frameworks to ensure performance, safety, and reliability of GenAI systems

Programming & Data Engineering

• Develop high-quality code in Python with strong hands-on experience in:
  • Pandas, NumPy, scikit-learn
  • PyTorch, TensorFlow, Transformers
  • FastAPI, LangChain, LlamaIndex
• Integrate GenAI solutions with enterprise applications via APIs, orchestration tools, and knowledge graphs
• Work with vector databases such as PGVector, Pinecone, MongoDB Atlas, Neo4j
• Design solutions for processing and managing large-scale unstructured datasets

Deployment & MLOps

• Deploy GenAI and ML models into production environments
• Implement and manage MLOps pipelines, including model evaluation and monitoring
• Build and maintain CI/CD pipelines using tools such as Jenkins, GitLab CI, Azure DevOps, or ArgoCD
• Ensure scalability, reliability, and performance of deployed AI systems

Cloud & Containerization

• Work with cloud-native architectures and services
• Deploy and manage containerized applications using Kubernetes or OpenShift
• Optimize performance and scalability in distributed environments

Required Skills & Qualifications

• 6–10 years of experience in application development, AI/ML, or systems analysis
• Strong foundation in Machine Learning, Data Science, and Statistics
• Hands-on experience with Generative AI, LLMs, and RAG pipelines (mandatory)
• Advanced Python programming skills
• Experience with cloud platforms and containerization technologies
• Strong understanding of software engineering best practices and Agile methodologies

Preferred Qualifications

• Experience in enterprise-scale AI implementations
• Familiarity with knowledge graphs and semantic search
• Exposure to AI governance, ethics, and responsible AI practices

Why Join Virtusa?

• Opportunity to work on cutting-edge Generative AI projects
• Collaborative and innovation-driven work environment
• Access to global clients and enterprise-scale challenges
• Continuous learning and career growth opportunities