Generative AI Engineer

JOB DESCRIPTION

Experience : 3 - 10 Yrs

Location : Bengaluru

Designation : Gen AI Engineer / Princial Engineer - AI

Key Responsibilities

• Architect, build, and deploy agentic AI systems using frameworks such as LangGraph, Google ADK,Autogen, Semantic Kernel, CrewAI, and LangChain.
• Design and implement RAG pipelines leveraging vector databases (OpenSearch, Pinecone, FAISS, or Weaviate).
• Develop modular and reusable AI agent architectures for dynamic reasoning and tool orchestration.
• Integrate and fine-tune foundation models (GPT, Claude, Gemini, Mistral, Llama, etc.) for domain-specific tasks.
• Work with APIs, embeddings, and context optimization for large-scale AI workflows.
• Collaborate with platform, data, and product teams to ensure robust integration and deployment.
• Implement observability, performance tracking, and continuous evaluation of model and agent behavior.
• Stay up to date with the latest research and open-source developments in LLMs, agents, and cognitive frameworks.
• Mentor and guide junior engineers on prompt design, agent architecture, and optimization techniques.

Required Skills & Experience

• 3–10 years of total experience in AI / ML engineering, including at least 2 years in Generative AI.
• Proven expertise with agentic frameworks — LangGraph, Google ADK, Semantic Kernel, CrewAI, LangChain, or similar.
• Strong programming skills in Python and familiarity with microservice or API- based systems.
• Hands-on experience with LLMs, vector search, and retrieval-augmented generation ( ) architectures.
• Good understanding of prompt engineering, model evaluation, and context optimization.
• Experience with cloud platforms (AWS, Azure, or GCP) and containerized deployments.
• Exposure to model fine-tuning, LoRA, or custom embedding generation.
• Build multimodal content generation workflows:
• Text → Image (Stable Diffusion, Runway, Sora, GPT, Midjourney APIs)
• Image → Image / Video (image transformation, video synthesis)
• Text → Video (Veo, Sora, Pika Labs, Runway ML, or similar)
• Text → Audio / Speech (TTS systems, diffusion-based audio models)

Good to Have

• Knowledge of multimodal AI (text, image, audio, video).
• Experience building or contributing to internal agent SDKs and AI developer platforms.
• Understanding of tool-augmented reasoning, graph-based agent workflows, and memory architectures.
• Familiarity with data governance, hallucination control, and AI safety best practices.
• Experience optimizing inference latency and cost for production-scale models.