We are looking for a passionate and experienced Generative AI Engineer to design, implement, and scale intelligent AI agents and applications. You will work on architecting agentic systems powered by LLMs, retrieval-augmented generation (RAG), and reasoning frameworks. The ideal candidate is someone who stays current with the fast-evolving GenAI ecosystem and can transform advanced research into production-grade solutions.
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
5–10 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.
Soft Skills
Strong problem-solving and analytical thinking abilities.
Excellent communication and cross-functional collaboration skills.
Self-driven, with a focus on ownership and innovation.
Ability to translate complex technical ideas into practical, scalable implementations.
Why Join Us
Work at the forefront of agentic and generative AI innovation.
Collaborate with a highly skilled AI research and engineering team.
Shape the architecture of next-generation intelligent systems.
Opportunity to lead high-impact projects with cutting-edge LLM and reasoning frameworks.
Competitive compensation, flexible work setup, and a culture centered on innovation and technical excellence.