Job Description :
Key Responsibilities :
- Define and own the companys AI vision, roadmap, and long-term strategy. Lead end-to-end AI initiatives from ideation to implementation and scaling.
- Drive the adoption of AI technologies across business units to enhance operational efficiency and customer experience.
- Stay ahead of AI trends, emerging technologies, and industry best practices to ensure continuous innovation.
- Oversee architecture, design, and deployment of AI / ML, deep learning, NLP, GenAI, and computer vision solutions.
- Ensure development of scalable, secure, and production-grade AI systems.
- Review technical designs, code, and architecture to ensure high-quality standards.
- Guide teams in model selection, experimentation frameworks, MLOps, and performance optimization.
- Lead, mentor, and grow a high-performing team of ML Engineers, Data Scientists, MLOps Engineers, and AI Researchers.
- Build a culture of innovation, experimentation, and accountability within the AI team.
- Manage resource planning, competency development, and project execution.
- Work closely with Product, Engineering, Data, Cloud, and Business teams to ensure alignment of AI initiatives with organizational objectives.
- Translate complex AI capabilities into business use cases and measurable outcomes.
- Provide thought leadership to executive stakeholders, influencing data-driven decisions.
- Establish AI governance frameworks, ethical AI guidelines, and responsible AI best practices.
- Ensure compliance with privacy, security, and regulatory requirements (GDPR, HIPAA, etc.).
- Oversee model monitoring, drift detection, retraining pipelines, and audit processes.
- Drive research initiatives in LLMs, agentic AI, reinforcement learning, multimodal models, and emerging AI technologies.
- Lead POCs and experimentation to evaluate feasibility of new AI use cases.
Qualifications & Skills :
12- 15 years of overall experience with at least 8+ years in AI / ML leadership roles.Advanced proficiency in Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn), and LLM technologies.Expertise in designing and scaling AI systems on cloud platforms (AWS, Azure, GCP).Strong understanding of MLOps, CI / CD for ML, data pipelines, and model lifecycle management.Experience building AI products, recommendation engines, predictive models, GenAI applications, and intelligent automation solutions.Deep understanding of data engineering, distributed computing, and big data technologies (Spark, Kafka, Databricks).Exceptional communication, stakeholder management, and strategic leadership skills.Strong problem-solving mindset with the ability to convert business challenges into AI opportunities.Preferred Qualifications :
Masters or PhD in Computer Science, AI / ML, Data Science, or related field.Experience working in product-based or large-scale enterprise environments. Publications, patents, or open-source contributions in AI / ML.(ref : hirist.tech)