Description

You will develop and deploy agentic AI systems using LLMs and modern AI frameworks.

Responsibilities

• Design, develop, and deploy agentic AI systems leveraging LLMs and modern AI frameworks.
• Integrate GenAI models into full-stack applications and internal workflows.
• Collaborate on prompt engineering, model fine-tuning, and evaluation of generative outputs.
• Build reusable components and services for multi-agent orchestration and task automation.
• Optimize AI inference pipelines for scalability, latency, and cost efficiency.

Required Skills

• 4–8 years of software engineering experience, with 1–2 years specifically in AI/ML or GenAI systems in production.
• Hands-on Python experience for AI/ML model integration.
• Experience with LLM frameworks (LangChain, LlamaIndex required).
• Exposure to agentic frameworks (Langgraph, AutoGen, CrewAI required).
• Understanding of Git, CI/CD, DevOps, and production-grade GenAI deployment practices.
• Experience building AI APIs, embeddings, vector search, and integrating them into applications.
• Experience fine-tuning open-source models (LLaMA, Mistral, etc.) or working with OpenAI APIs.

Preferred Skills

• Familiarity with Google Cloud Platform (GCP) including Vertex AI, Cloud Run, and GKE.
• Exposure to multi-modal AI systems (text, image, or voice).

Key Skills

Education

Any Graduate