Senior Manager - Data Science

Company Description

Organizations everywhere struggle under the crushing costs and complexities of “solutions” that promise to simplify their lives. To create a better experience for their customers and employees. To help them grow. Software is a choice that can make or break a business. Create better or worse experiences. Propel or throttle growth. Business software has become a blocker instead of ways to get work done.

There’s another option. Freshworks. With a fresh vision for how the world works.

At Freshworks, we build uncomplicated service software that delivers exceptional customer and employee experiences. Our enterprise-grade solutions are powerful, yet easy to use, and quick to deliver results. Our people-first approach to AI eliminates friction, making employees more effective and organizations more productive. Over 72,000 companies, including Bridgestone, New Balance, Nucor, S&P Global, and Sony Music, trust Freshworks’ customer experience (CX) and employee experience (EX) software to fuel customer loyalty and service efficiency. And over 4,500 Freshworks employees make this possible, all around the world.

Fresh vision. Real impact. Come build it with us.

Job Description

Freshworks is looking for a strategic and technically proficient Senior Manager in our Applied AI team. This team serves as the "Architects of Excellence" for every AI initiative within the company. You will lead a high-impact squad of around 10 Data Scientists and AI Engineers responsible for ensuring that our AI agents and models are performant, secure, and continuously evolving.

As the primary stakeholder for AI design and deployment, your team’s mission is to bridge the gap between experimental AI and industrial-grade, customer-ready products. You will oversee the entire lifecycle of AI excellence—from initial design sign-offs and sophisticated evaluation frameworks to advanced model optimization and MLOps.

Responsibilities

Team Leadership & Governance

• Lead and mentor a team of around 10 Data Scientists and AI Engineers, fostering a culture of technical rigor and continuous innovation.

• Act as the primary stakeholder for all AI activities across the organization, reviewing architectural designs and providing the final technical sign-off.

• Define and enforce standards for model selection strategies and effective prompting to ensure AI use cases are solved with the right tool for the job.

Evaluation & Quality Engineering

• Own the end-to-end Evaluation (Eval) strategy for AI use cases.

• Architect and implement robust frameworks for both build-time evals and production-time evals to enable data-driven continuous learning loops.

• Monitor production metrics for AI deployments (agents, models, and prompts) to identify and execute improvements.

Model Optimization & Compliance

• Drive the creation of top-tier models through fine-tuning, distillation, and Reinforcement Learning (RL) to achieve the optimal balance of price, performance, and power (reasoning).

• Ensure all models are secure and that data training pipelines remain strictly compliant with global data privacy standards.

MLOps & Deployment Excellence

• Oversee sophisticated deployment strategies including shadow testing, A/B testing, and gradual rollouts.

• Manage rollback protocols and conduct deep-dive field performance analysis of AI Agents to ensure seamless user experiences.

Qualifications

Qualifications

• Education: Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).

• Experience: 10+ years of professional experience in AI/ML with 2+ years in Agentic AI

• Leadership: Minimum of 3+ years in a formal people management role, with a proven track record of scaling and mentoring technical teams.

• Domain Expertise: Deep understanding of Large Language Models (LLMs), Generative AI lifecycles, and traditional ML foundations.

Skills Inventory

Required Skills

• Model Engineering: Proficiency in model fine-tuning, distillation techniques, and RL/RLHF.

• Evaluation Frameworks: Expertise in building automated eval pipelines for LLMs (e.g., using Arize, RAGAS, DeepEval, or custom benchmarking).

• MLOps Mastery: Practical experience with shadow deployments, A/B testing, and managing production AI agents at scale.

• Strategic Prompting: Advanced knowledge of prompt engineering patterns (Chain of Thought, ReAct, etc.).

• Security & Compliance: Strong grasp of AI security vulnerabilities (prompt injection, data leakage) and data compliance (GDPR/SOC2).

Good-to-Have Skills

• Infrastructure: Familiarity with cloud-native AI infrastructure (AWS Bedrock, Azure AI, or GCP Vertex AI).

• Resource Optimization: Experience in optimizing models for "Power" (reasoning capability) vs. "Price" (token cost) vs. "Performance" (latency).

• Product Thinking: Ability to translate complex AI metrics into business impact and customer satisfaction scores.

Public Contribution: Active participation in the AI research community or contributions to open-source AI projects.

Additional Information

At Freshworks, we have fostered an environment that enables everyone to find their true potential, purpose, and passion, welcoming colleagues of all backgrounds, genders, sexual orientations, religions, and ethnicities. We are committed to providing equal opportunity and believe that diversity in the workplace creates a more vibrant, richer environment that boosts the goals of our employees, communities, and business. Fresh vision. Real impact. Come build it with us.