What are the responsibilities and job description for the Generative AI Engineer position at Skywaves Rise?
As a 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
- 8 years of software engineering experience with at least 3 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, Google ADK, is a must)
- Understanding of Git, CI/CD, DevOps, and production-grade GenAI deployment practices.
- Familiarity with Google Cloud Platform (GCP) — e.g. Vertex AI, Cloud Run, and GKE.
Good-to-Have
- 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