Team Lead Artificial Intelligence

Experience Required:

Minimum 5–7 years in AI/ML Engineering, with expertise in computer vision, video streaming, multi-agent systems, large language models (LLMs), Retrieval-Augmented Generation (RAG), and multi-modal AI systems.

Job Summary:

We are seeking a highly skilled AI Engineering Manager / AI Solution Architect to lead the design, development, and deployment of cutting-edge AI-powered ...solutions.

This role requires a strategic leader with deep technical expertise across computer vision, real-time video analysis, multi-agent frameworks, LLMs, and scalable AI architectures for both cloud and edge environments.

The ideal candidate will be responsible for architecting robust systems, mentoring technical teams, and driving innovation aligned with business objectives.

Key Responsibilities:

Leadership & Strategic Direction

• Lead, mentor, and grow a high-performing team of AI engineers, data scientists, and developers.

• Define the strategic direction of AI initiatives in collaboration with stakeholders and product teams.

• Ensure AI roadmaps are aligned with product goals, business needs, and future scalability.

AI Architecture & Model Development

• Architect and implement scalable AI systems across computer vision, video analytics, and multi-agent environments.

• Design, develop, and optimize deep learning models for object detection, instance segmentation, and pose estimation using YOLOv5/v8, Mask R-CNN, Detectron2, or similar architectures.

• Develop complex video analysis pipelines capable of identifying events and behaviors, integrating Visual Language Models (VLMs) for enhanced contextual understanding.

• Build robust training pipelines covering data ingestion, preprocessing, augmentation, training, evaluation, and hyperparameter tuning.

• Optimize models for deployment across CPU, GPU, and NPU environments, with a focus on real-time inference and edge AI capabilities.

LLM & Agentic AI Systems

• Architect and deploy large language models (LLMs) such as GPT, Claude, or DeepSeek in production-grade systems.

• Design and implement Retrieval-Augmented Generation (RAG) pipelines to improve contextual accuracy.

• Develop agentic AI applications with autonomous and collaborative multi-agent systems using frameworks such as CrewAI and LangChain.

• Implement prompt engineering strategies and intelligent workflows for seamless agent orchestration.

• Integrate memory/state management tools (e.g., Redis, Pinecone) to enable situational and conversational continuity.

Software Engineering & DevOps

• Write clean, modular, test-driven Python code using best practices in AI model development and deployment.

• Implement and maintain CI/CD pipelines for automation of training, testing, and model deployment.

• Collaborate with DevOps to ensure efficient monitoring, scaling, and reliability of AI services.

• Monitor production pipelines, debug edge cases, and continuously improve inference performance and reliability.

Collaboration & Cross-functional Integration

• Partner with Product Managers, Researchers, and Engineers to define product requirements and integrate AI features effectively.

• Communicate complex technical solutions to both technical and non-technical stakeholders.

• Ensure technical documentation and codebase meet quality and compliance standards.

Innovation & R&D

• Stay up to date with emerging research and technologies in AI, LLMs, agentic systems, and multi-modal architectures.

• Drive in-house experimentation, proof-of-concepts, and adoption of breakthrough technologies.

• Contribute to open-source projects and foster a culture of innovation within the team.

Required Skills & Qualifications:

• Education: Bachelor’s or Master’s in Computer Science, AI, Data Science, or related field.

• Technical Expertise:

• Advanced experience with computer vision, video analysis, LLMs, RAG pipelines, and multi-agent architectures.

• Proficiency with Python, PyTorch, TensorFlow, OpenCV, FFmpeg, aiortc, GStreamer, YOLO, and other ML/vision libraries.

• Hands-on with web scraping tools (BeautifulSoup, Selenium, Scrapy) for data collection and model training.

• Strong experience in model deployment on cloud (e.g., OVH, AWS, GCP) and edge platforms.

• Project Management: Proven experience managing complex AI projects using Agile methodologies.

• Soft Skills: Exceptional communication, leadership, problem-solving, and decision-making skills.

Preferred Qualifications:

• Experience with multi-modal AI systems and cross-domain model integration.

• Familiarity with edge AI deployment, quantization, and model compression techniques.

• Contributions to open-source AI or ML research communities. Show full description