Overview
As a Senior Generative AI Engineer, you’ll be a core member of this pod, building and integrating
agentic systems powered by cutting-edge LLM and GenAI technologies. You’ll work closely
with Tech Leads and Full Stack Engineers to turn AI capabilities into production-ready enterprise
solutions.
Key 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.
● Participate in architectural discussions, contributing to the pod’s technical roadmap.
Core Skills & Experience
Must Haves
● 7+ years of software engineering experience with at least 2 years in AI/ML or GenAI systems in production
● Hands-on experience with Python only for AI/ML model integration.
● Experience with LLM frameworks (LangChain, LlamaIndex is a must
● Exposure to agentic frameworks (Langgraph, AutoGen, CrewAI is a must
● Understanding of Git, CI/CD, DevOps, and production-grade GenAI deployment practices.
Nice-to-Have
● Familiarity with Google Cloud Platform (GCP) — especially Vertex AI, Cloud Run, and GKE.
● 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.
● Exposure to multi-modal AI systems (text, image, or voice).
● Familiarity with Low-Code/No-Code tools (e.g., AppSheet) for workflow integration.
