About the Role
Principal Responsibilities:
Deliver AI Capabilities: Lead the development and delivery of AI-powered solutions to support internal business needs, ensuring alignment with organizational goals and objectives.
AI Advisory Role: Act as a key AI advisor for internal stakeholders, educating and promoting the use of AI across different teams to solve business problems and drive operational efficiencies.
Technical Leadership: Provide hands-on technical leadership to a team of data scientists and full-stack developers, guiding the team on architecture, design patterns, and implementation best practices. Ensure smooth day-to-day operations, code quality, and technical direction. Participate in the design and implementation of supporting infrastructure services to ensure scalability and robustness.
Collaborate Across Teams: Partner with various internal departments to gather and document detailed requirements for AI features. Translate business needs into technical requirements that can be efficiently executed by the development team.
AI Model Development Best Practices: Establish and maintain best practices for the full AI model development lifecycle, including data preparation, model training, model evaluation, version control, and MLOps for the deployment and monitoring of AI models.
Agile Methodology: Promote and implement best practices for software development, including coding standards, code reviews, source management, build automation, and continuous integration/continuous deployment (CI/CD) pipelines.
Team Building & Hiring: Play a critical role in hiring, mentoring, and developing a high-performing team of data scientists and full-stack developers. Foster a culture of continuous learning and development within the team.
Requirements
Experience in Managing projects: Minimum of 5+ years of experience as a technical manager, team lead, or in a similar leadership role overseeing data scientists and developers.
Technical Experience: 7+ years of experience in software development with deep knowledge of both front-end and back-end technologies, ensuring a comprehensive understanding of web application architecture. Experience in Data science related work with strong focus on delivering AI-driven solutions.
AI/ML Proficiency: In-depth knowledge and familiarity with a wide range of AI/ML algorithms, including statistical models, probabilistic methods, deep learning architectures, and Large Language Models (LLMs). Familiarity with Retrieval-Augmented Generation (RAG) architecture is a strong plus.
Cloud Experience: Practical experience with cloud-based data warehouse technologies such as Snowflake, AWS Redshift, Google BigQuery, or other similar platforms.
Technical Tools & Frameworks: Proficiency in programming languages such as Python, Java, or similar. Experience with machine learning libraries (e.g., TensorFlow, PyTorch), MLOps tools, version control (e.g., Git), and CI/CD pipelines. Agile & Project Management: Prior experience working in Agile development environments. Proficiency with project management tools such as JIRA, Confluence, or equivalent.
Communication & Collaboration: Excellent verbal and written communication skills. Proven ability to work cross-functionally with business teams, developers, and data scientists.
Problem-Solving: Strong analytical skills with the ability to identify and resolve complex technical and business problems.