Generative AI Engineer

We’re looking for a Generative AI Engineer to join our innovation pod, focused on designing and integrating agentic AI systems built on the latest LLM and GenAI technologies. You’ll collaborate with technical leads and full-stack engineers to bring intelligent, production-grade AI capabilities to enterprise applications. Vetting Process 1. Technical Interview 1. 15-Minute Delivery Connect 1. Onsite (Face-to-Face) Interview – Richardson, TX (1 Hour, Client Round) Key Responsibilities • Design, develop, and deploy agentic AI systems using state-of-the-art LLM frameworks. • Integrate Generative AI models into full-stack applications and internal business workflows. • Collaborate on prompt engineering, model fine-tuning, and output evaluation. • Build reusable AI components for multi-agent orchestration and task automation. • Optimize AI inference pipelines for scalability, latency, and cost efficiency. • Contribute to technical architecture and the long-term AI roadmap. Core Skills & Experience Must Have • 4–8 years of software engineering experience (with at least 1–2 years in AI/ML or GenAI). • Strong Python development background (for AI/ML model integration). • Hands-on experience with LLM frameworks – LangChain and LlamaIndex (Required). • Practical exposure to agentic frameworks – LangGraph, AutoGen, or CrewAI (Required). • Working knowledge of Git, CI/CD, DevOps, and production-grade GenAI deployment. Nice to Have • Experience with Google Cloud Platform (GCP) – especially Vertex AI, Cloud Run, or GKE. • Familiarity with AI APIs, embeddings, vector databases, and search integrations. • Experience with fine-tuning open-source models (LLaMA, Mistral, etc.) or OpenAI API integration. • Exposure to multi-modal AI systems (text, image, or voice). • Experience with Low-Code/No-Code tools (e.g., AppSheet) for workflow automation. Preferred Academic Background Candidates from strong academic institutions with a background in Computer Science, AI/ML, or related fields are preferred.