Generative AI Engineer

13 hours ago

Bengaluru, Karnataka, India Mastech Digital Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Role Overview:

Looking for a Generative AI Specialist with 5-7 years of experience focusing on state-of-the-art generative AI technologies including large language models (LLMs) and agentic AI. The candidate will act as a technical mentor, engaging with clients to develop advanced generative solutions and mentor junior team members.

Key Responsibilities:

  • Architect, fine-tune, and deploy Generative AI and LLM-based solutions for diverse industries.
  • Lead development of RAG pipelines, multi-agent orchestration, and generative workflows for automation.
  • Collaborate with clients to define problem statements, data strategies, and AI integration approaches.
  • Design and execute rapid prototypes and POCs using transformer-based and diffusion-based architectures.
  • Mentor junior engineers on LLM fine-tuning, prompt engineering, and API-based integration.
  • Continuously evaluate and adopt emerging open-source frameworks and foundation models (e.g., Llama, Claude, Gemini, Mistral).
  • Drive MLOps integration for generative AI solutions ensuring scalability, reproducibility, and compliance.

Requirements:

  • 5–7 years of overall AI experience, with at least 2–3 years dedicated to Generative AI and LLM-based systems.
  • Hands-on experience building RAG, conversational, or multi-agent-based AI architectures.
  • Expertise in fine-tuning, prompt optimization, and LLM orchestration.
  • Proven success in developing generative solutions for enterprise applications.
  • Excellent communication and technical mentoring skills.
  • Bachelor's/master's degree in computer science, AI, or related discipline

Desired Technical Skills & Tools:

  • Programming:
    Python, LangChain, LlamaIndex, Multi Agentic Systems
  • LLM Frameworks:
    OpenAI GPT series, Hugging Face Transformers, Anthropic Claude, Mistral, Llama 3, Agnos
  • Generative AI Tools:
    LangGraph, Vector Databases (Pinecone, FAISS, Chroma), PromptLayer, LangFuse
  • RAG & Agent Frameworks:
    Haystack, Semantic Kernel, AutoGen, CrewAI
  • MLOps & Deployment:
    Docker, Kubernetes, MLflow, Vertex AI, Azure OpenAI, AWS Bedrock
  • Data & Integration:
    REST APIs, Kafka, ElasticSearch, PostgreSQL, NoSQL, Data Lakes
  • Other Skills:
    Prompt Engineering, Model Evaluation Metrics, Hallucination Control, Knowledge Graphs, Context Management
  • Cloud & Infra:
    Azure AI Studio, AWS SageMaker, GCP GenAI Studio

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