Data Science Engineer - Agentic AI (6-8 yrs)

Role Overview :

We are seeking a seasoned Data Science professional to spearhead our next generation of intelligent systems. In this role, you will bridge the gap between complex machine learning research and scalable production environments, designing sophisticated Agentic AI workflows that redefine how our business interacts with data.

You will collaborate closely with cross-functional engineering teams, product managers, and executive stakeholders to translate ambiguous business challenges into high-impact AI solutions.

By leveraging cutting-edge frameworks, you will drive the development of autonomous agents and copilot experiences that significantly enhance operational efficiency and deliver tangible value to our global customer base.

Key Responsibilities :

- Architect and deploy advanced Agentic AI solutions using LangChain and LangGraph to automate complex decision-making processes for internal and external stakeholders.

- Lead the end-to-end development lifecycle of Copilot-style applications, ensuring seamless integration with existing enterprise ecosystems on Azure.

- Optimize large-scale machine learning models to improve predictive accuracy and system latency, directly impacting user experience and platform reliability.

- Mentor junior data scientists and engineers by fostering a culture of technical excellence, rigorous code reviews, and innovative problem-solving.

- Partner with product leadership to define the AI roadmap, ensuring that technical initiatives align with long-term business objectives and market demands.

Required Skillset :

- Demonstrated expertise in building and scaling production-grade AI systems, with a deep understanding of AIML architectures and modern LLM orchestration frameworks.

- Proven ability to design and implement complex workflows using LangChain and LangGraph to solve real-world business problems.

- Strong proficiency in deploying and managing AI workloads within the Azure cloud environment, ensuring security, scalability, and cost-efficiency.

- Exceptional communication skills with the ability to articulate complex technical concepts to non-technical stakeholders and influence decision-making at the leadership level.

- A strong academic foundation in Computer Science, Statistics, or a related quantitative field, complemented by a track record of continuous learning in the rapidly evolving AI landscape.

- High degree of self-motivation and adaptability, with the ability to thrive in a distributed, remote-first work environment while maintaining high standards of collaboration and output.