Description
The AI Technical Architect is responsible for designing, developing, and implementing advanced artificial intelligence solutions that address critical business challenges.
The role demands a deep understanding of AI technologies, architecture principles, and hands-on experience in building scalable AI systems. The ideal candidate will collaborate with cross-functional teams to deliver innovative solutions, ensuring alignment with organisational goals and industry best practices.
Key Responsibilities
- Lead the design and architecture of AI-driven platforms, ensuring scalability, security, and performance.
- Collaborate with stakeholders to understand business requirements and translate them into AI solutions.
- Evaluate and select appropriate AI frameworks, tools, and technologies for various use cases.
- Oversee the development, deployment, and integration of machine learning models and AI services.
- Establish best practices for AI development, including data governance, model management, and MLOps processes.
- Mentor and guide technical teams in the adoption and implementation of AI technologies.
- Stay updated with the latest advancements in AI, machine learning, and data science, and recommend relevant innovations.
- Ensure compliance with regulatory requirements, data privacy, and ethical AI standards.
- Prepare technical documentation, architectural diagrams, and reports as required.
Qualifications and Skills
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field. A PhD is an added advantage.
- 10+ years of experience in software architecture, with at least 3 years in AI/ML solution design and implementation.
- Strong proficiency in one or more programming languages (Python, Java, R, etc.) relevant to AI development.
- Hands-on experience with AI/ML frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn.
- Expertise in cloud platforms (Azure, AWS, GCP) and containerisation (Docker, Kubernetes) is highly desirable.
- Excellent understanding of data engineering, model deployment, and MLOps pipelines.
- Strong analytical, problem-solving, and communication skills.
- Ability to work collaboratively in a multicultural and distributed team environment.
Preferred Attributes
- Relevant AI certifications (e.g., Microsoft Certified: Azure AI Engineer Associate, Google Professional Machine Learning Engineer).
- Experience in developing AI solutions for Indian or international markets.
- Demonstrated ability to manage multiple projects and priorities effectively.
Preferred Skills
- Experience with deep learning architectures (CNNs, RNNs, LSTMs, Transformers).
- Familiarity with MLOps and CI/CD pipelines for model deployment and monitoring.
- Understanding of ethical AI practices and data privacy regulations.
- Published research papers or contributions to open-source AI projects.