Role Overview:

As a Technical Architect for Artificial Intelligence, you will serve as the strategic bridge between complex business challenges and cutting-edge AI solutions. You will lead the design and implementation of scalable, high-performance machine learning and Generative AI architectures, ensuring they align with enterprise-grade requirements. Working closely with cross-functional product teams, data scientists, and C-suite stakeholders, you will define the technical roadmap that drives innovation and operational efficiency. Your work will directly influence the companys competitive edge, transforming raw data into actionable intelligence and delivering transformative AI-driven experiences for our global customer base.

Key Responsibilities:

- Architect end-to-end AI and Machine Learning systems that integrate seamlessly into existing cloud infrastructure to enhance product scalability and reliability.

- Lead the adoption of Generative AI frameworks and Large Language Models (LLMs) to automate complex workflows and improve user engagement across our digital platforms.

- Collaborate with engineering leadership to establish best practices for MLOps, ensuring robust model deployment, monitoring, and lifecycle management.

- Translate ambiguous business requirements into precise technical specifications, enabling the development team to build solutions that solve critical market problems.

- Mentor senior engineering talent and foster a culture of technical excellence, ensuring the team stays ahead of the curve in the rapidly evolving AI landscape.

Required Skillset:

- Demonstrated expertise in designing and deploying large-scale AI/ML architectures, with a deep understanding of model training pipelines and inference optimization.

- Proven ability to implement Generative AI solutions, including fine-tuning LLMs and building RAG-based applications, to address specific business use cases.

- Exceptional communication skills, with the ability to articulate complex technical strategies to non-technical stakeholders and influence executive decision-making.

- Strong leadership experience in managing high-performing technical teams, fostering collaboration, and driving consensus across diverse organizational units.

- A solid academic foundation in Computer Science, Mathematics, or a related quantitative field, typically supported by an advanced degree from a premier institution.

- Ability to thrive in a hybrid work environment in Bangalore, balancing independent architectural deep-dives with active, in-person collaboration with local teams.