Role Overview :

We are seeking a seasoned Data Engineer to spearhead our transition into the next generation of intelligent systems by building robust infrastructure for Agentic AI. In this role, you will design and maintain the complex data pipelines and orchestration layers required to power autonomous agents that reason, plan, and execute tasks. You will collaborate closely with AI research scientists, product managers, and cross-functional engineering teams to bridge the gap between raw data and actionable intelligence. By architecting scalable, high-performance systems, you will directly influence the reliability and effectiveness of our AI-driven products, ensuring our business remains at the forefront of the generative AI landscape in Bangalore.

Key Responsibilities :

- Architect and deploy scalable data ingestion and processing frameworks that support high-throughput LLM training and real-time inference workflows to ensure seamless agent performance.

- Design sophisticated orchestration layers for Agentic AI, enabling agents to interact with external tools, databases, and APIs to solve complex, multi-step user problems.

- Optimize data retrieval systems, including vector databases and RAG (Retrieval-Augmented Generation) pipelines, to enhance the contextual accuracy and reasoning capabilities of our AI models.

- Collaborate with data science and engineering teams to establish robust MLOps practices, ensuring that agentic workflows are monitored, reproducible, and compliant with enterprise security standards.

- Mentor junior engineers and lead technical initiatives to improve system latency and data quality, directly impacting the end-user experience and operational efficiency of our AI platforms.

Required Skillset :

- Demonstrated mastery in Python for building production-grade data pipelines, coupled with deep expertise in AWS cloud services such as S3, EMR, Redshift, and SageMaker for scalable infrastructure.

- Proven ability to design and manage vector databases and advanced indexing strategies that facilitate efficient information retrieval for Large Language Models.

- Strong conceptual understanding of Agentic AI frameworks and the ability to integrate LLMs into complex, autonomous workflows that deliver measurable business value.

- Exceptional communication skills, with the ability to translate complex technical architectures into clear strategies for non-technical stakeholders and cross-functional leadership.

- A proactive, problem-solving mindset with the adaptability to thrive in a fast-paced, hybrid work environment in Bangalore, where rapid iteration and continuous learning are the norms.

- A solid academic foundation in Computer Science, Engineering, or a related quantitative field, providing the theoretical rigor necessary to tackle challenging data engineering problems.