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Senior AI Engineer
On-siteFull-timeAI EngineeringIT Services
Lead the end-to-end design, development, optimization, and deployment of production-grade AI systems. Projects focus on either LLM-based agentic systems or computer vision, including real-time video analytics, depending on expertise and business needs.
Responsibilities
- Lead the design and development of AI systems for agentic LLM applications or computer vision
- Own delivery from architecture and prototyping through production deployment
- Optimize model latency, throughput, and performance on GPU platforms
- Design clean, maintainable, and scalable AI software architectures
- Translate customer and product requirements into technical solutions
- Mentor junior engineers and contribute to technical best practices
- Evaluate tools, models, and frameworks and guide their adoption
Requirements
- Bachelor’s or master’s degree in Computer Science, Electrical Engineering, or a related field
- At least 4 years of experience in software engineering and applied AI, or equivalent experience
- Strong Python skills and experience with modern AI frameworks
- Track record of delivering production-grade AI systems
- Understanding of deep learning architectures, including CNNs and transformers
- Experience with system design, debugging, and performance optimization
- Experience with either LLM and agentic systems or computer vision and deep learning
- For LLM-focused work: experience building agentic workflows and deploying or optimizing open-source LLMs
- For computer vision-focused work: experience with detection, segmentation, tracking, and video pipelines
Nice to have
- Experience with CUDA, TensorRT, Triton, or inference microservices
- GPU performance profiling and optimization experience
- Background in high-performance or low-latency systems
- Experience mentoring engineers or leading technical initiatives
Benefits
- Ownership of complex, high-impact AI projects
- Work with advanced GPU and AI technologies
- Influence over architecture, tooling, and technical direction
- Collaborative, engineering-driven culture
- Technical leadership and professional growth opportunities
- Real-world, production-scale AI challenges