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.

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