Data Science Manager
Location Hyderabad
Major Responsibilities:
Lead the design and implementation of sophisticated agentic AI systems, including multi-agent orchestration and autonomous workflows. Define architectural standards for agent development, including tool integration, memory management, and inter-agent communication protocols
Establish comprehensive evaluation frameworks for agentic systems, measuring task completion, reasoning quality, and safety compliance. Design and implement guardrails for autonomous agents, including behavioural boundaries, output validation, and fallback mechanisms
Drive hands-on prototyping of complex agent systems while providing technical oversight to development teams. Create testing methodologies for agent reliability, including edge case handling, adversarial testing, and performance benchmarking
Balance technical depth with strategic thinking to identify where agentic AI can transform business processes. Lead technical reviews of agent architectures, personally debugging complex multi-agent interaction issues
Deep technical knowledge of agent evaluation metrics: task success rates, reasoning traces, tool-use efficiency, and safety violations. Proven experience implementing production guardrails: content filtering, action limitations, human-in-the-loop systems
Strong understanding of agent architectures: ReAct, Plan-and-Execute, Reflexion, and emerging patterns. Experience with agent memory systems: episodic memory, semantic memory, and working memory implementations
Ability to code review and debug complex agent behaviors, including emergent properties and unexpected interactions. Track record of building teams while maintaining hands-on technical involvement
Minimum Requirements:
Education (minimum/desirable): Masters degree in relevant field required; MBA or PhD preferred
7+ years in AI/ML with maximum 3 years in generative AI and demonstrated expertise in agentic systems. Hands-on coding experience with complex agentic AI implementations, including multi-agent systems and tool-use agents.
Ability to balance operational execution with high-level strategic thinking, driving both immediate results and long-term GenAI transformation
Strong capability to work collaboratively with cross-functional teams, including Marketing, Field Sales, Data Enablement Platform Teams to ensure GenAI solutions meet business needs
Excellent communication skills, capable of effectively collaborating with senior leadership and board members on AI strategy
Ability to thrive in a fast-paced, dynamic environment and lead teams through changing business needs and priorities. Hands-on experience with agent observability and monitoring systems
Deep understanding of safety considerations for autonomous agents, including alignment techniques. Experience evaluating and implementing third-party agent frameworks and platforms
Track record of defining guardrail strategies that balance capability with safety. Published work or open-source contributions in agentic AI space preferred
