AI Engineer

We are looking for an AI Engineer to build AI-native capabilities within GRID, moving beyond traditional automation to intelligent, context-aware systems powered by LLMs, RAG pipelines, and agentic workflows. You will play a key role in shaping how AI integrates with operational systems, enabling real-time decisioning, workflow automation, and intelligent insights at scale.

Requirements

• Strong experience in building and developing Data Science and Machine Learning applications, including: Regression models, Predictive analytics, Time series forecasting, and Model evaluation and optimization.
• Hands-on expertise in developing Agentic AI applications using modern orchestration frameworks such as LangChain, LangGraph, Deep Agents, Multi-agent workflows, and autonomous systems.
• Solid experience in Computer Vision applications, including: Object detection, OCR systems, Image processing pipelines, Real-time vision inference systems.
• Strong understanding of AI/ML Ops (AIOps/MLOps), including: Model development lifecycle, Training pipelines, CI/CD for AI systems, Containerization and orchestration, Cloud/GPU deployment, Monitoring, scaling, and production optimization.
• Deep expertise in Large Language Models (LLMs), including LLM deployment and serving, Cost optimization and inference efficiency, Context engineering and prompt orchestration, RAG pipelines and vector databases, Fine-tuning and evaluation strategies.
• Experience integrating Voice AI systems, including: Speech-to-Text (STT), Text-to-Speech (TTS), Real-time audio streaming, Voice agent architectures, and Conversational AI systems.

Preferred Technical Stack

• Python, FastAPI, Flask, Async Programming.
• PyTorch / TensorFlow.
• Docker, Kubernetes, jenkins.
• Redis, Kafka, celery, Vector Databases.
• AWS / GCP / Azure.
• WebRTC / WebSocket-based streaming systems.

Additional Expectations

• Ability to architect scalable AI systems end-to-end.
• Strong debugging and production troubleshooting skills.
• Experience handling performance optimization and low-latency AI systems.
• Ability to work across research, engineering, and deployment layers.
• Strong communication and technical leadership skills. This job was posted by Hithyshi H A from WorkOnGrid.