AI Lead - Onshore

AI Strategy & Leadership 

• Develop and execute the company’s AI strategy aligned with business goals and product roadmap. 

• Lead cross-functional AI initiatives from concept to deployment, ensuring measurable value. 

• Manage and mentor a team of AI/ML professionals, providing technical direction and career development. 

• Stay current with emerging AI trends, LLM technologies, and best practices to guide innovation. 

Technical Oversight & Architecture 

• Architect and design scalable AI/ML solutions, including models, pipelines, and deployment infrastructure. 

• Oversee development of machine learning models, including training, evaluation, tuning, and productionization. 

• Ensure AI systems meet performance, reliability, security, and compliance requirements. 

• Work with engineering teams to integrate AI models into production applications and workflows. 

Project Delivery & Collaboration 

• Partner with Product, Data, Engineering, and UX teams to identify AI opportunities and translate them into actionable projects. 

• Lead technical reviews, roadmap planning, and prioritization for AI initiatives. 

• Ensure high-quality documentation for models, datasets, and pipelines. 

Data & Model Governance 

• Establish best practices for data management, model governance, versioning, monitoring, and ethical AI use. 

• Implement processes for model testing, retraining, bias detection, and drift monitoring. 

• Ensure adherence to regulatory and compliance standards related to AI and data privacy. 

Performance & Optimization 

• Analyze performance metrics, user feedback, and business impact to improve AI-driven features. 

• Continuously benchmark new tools, frameworks, and LLM technologies for potential adoption. 

• Drive experimentation frameworks (A/B testing, reinforcement learning, prompt optimization, etc.) for better model outcomes. 

Qualifications Required 

• Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, Data Science, or related field. 

• 7–10+ years of experience in AI/ML engineering, data science, or related roles. 

• Proven experience leading AI teams or large-scale AI initiatives. 

• Strong proficiency in Python, machine learning frameworks (TensorFlow, PyTorch, Sklearn), and data engineering tools. 

• Experience with LLMs, generative AI, and prompt engineering. 

• Hands-on experience with cloud platforms (AWS, GCP, Azure) and MLOps tools (Kubeflow, MLflow, SageMaker). 

• Strong understanding of data structures, algorithms, model optimization, and deployment best practices. 

Preferred 

• Experience building conversational AI, recommendation engines, predictive analytics, or intelligent automation systems. 

• Familiarity with vector databases, embeddings, retrieval-augmented generation (RAG), and LLM fine-tuning. 

• Experience with distributed computing frameworks (Spark, Ray). 

• Certifications in AI/ML, cloud, or data engineering. 

• Strong understanding of responsible AI, fairness, and regulatory requirements