Position Summary
We are seeking a highly experienced Senior AI Technical Leader to drive the design, development, and deployment of advanced AI solutions addressing complex business challenges. This role will lead enterprise-level AI initiatives across domains such as Natural Language Processing (NLP), Computer Vision, Recommendation Systems, and Predictive Analytics, while shaping technical strategy and establishing best practices.
Key Responsibilities
- Lead the design, development, and delivery of scalable AI/ML solutions aligned with business objectives
- Serve as a subject matter expert in applied AI, influencing enterprise-wide strategy
- Drive large-scale AI transformation initiatives across multiple business functions
- Collaborate with cross-functional stakeholders to identify and implement high-impact AI use cases
- Oversee end-to-end ML lifecycle: data preparation, model training, evaluation, deployment, and monitoring
- Ensure production-grade deployment with focus on scalability, performance, and reliability
- Translate cutting-edge AI research into practical, business-driven solutions
- Implement and promote responsible AI practices (fairness, transparency, security)
- Stay updated with emerging AI trends, tools, and frameworks
Required Qualifications
- 5+ years of software engineering experience (Python, C#, Java, C++, or similar)
- 2+ years hands-on experience with ML frameworks (PyTorch, TensorFlow)
- Strong experience with LLMs, Generative AI, or agent-based frameworks
- Proven track record delivering enterprise-scale AI/ML solutions on cloud platforms (AWS, Azure, or GCP)
- Deep understanding of ML algorithms, deep learning, and optimization techniques
- Experience with MLOps tools (Docker, Kubernetes, MLflow, etc.)
- Ability to convert research concepts into production-ready systems
- Strong stakeholder communication and leadership skills
- Bachelor’s degree in Computer Science, AI, ML, or related field
Preferred Qualifications
- Master’s or Ph.D. in AI, Machine Learning, Data Science, or related field
- Experience with transformers, edge AI, federated learning, or real-time inference
- Contributions to open-source AI projects, research publications, or patents
- Experience with enterprise productivity and collaboration tools