We are seeking skilled and motivated AI Engineering professionals to build, deploy, and optimize AI-powered applications, machine learning models, LLM workflows, automation systems, and scalable AI infrastructure.
The ideal candidates should have strong knowledge of Python, AI/ML systems, LLM integration, APIs, backend development, cloud infrastructure, databases, MLOps, and modern software development practices.
This role is suitable for candidates interested in working across AI product development, machine learning model deployment, prompt engineering, agentic workflows, RAG pipelines, DevOps/MLOps, and production-ready AI systems.
Key Responsibilities
- Build and integrate AI-powered applications into software products.
- Design, train, deploy, and optimize machine learning models.
- Develop scalable backend systems for AI-heavy features.
- Build and optimize LLM workflows, prompts, and RAG pipelines.
- Develop agentic workflows using tool-calling, SQL, and multi-step reasoning.
- Design and maintain MLOps and CI/CD pipelines for AI model lifecycle management.
- Manage cloud-native infrastructure using AWS, Azure, or GCP.
- Deploy containerized AI workloads using Docker and Kubernetes.
- Monitor model performance, infrastructure health, data drift, and system reliability.
- Optimize model serving, inference latency, and application performance.
- Build data pipelines for cleaning, preprocessing, and managing high-volume datasets.
- Implement AI security, data privacy, and reliability standards.
- Collaborate with product, engineering, and business teams to deliver AI-driven solutions.
