Data Science Lead

Key Responsibilities

• Lead the design and development of Agentic AI systems for automated incident triage, investigation, and proactive decision support
• Architect multi-agent orchestration frameworks using platforms such as AutoGen, LangChain, or Semantic Kernel
• Design and implement universal integration layers using APIs, webhooks, REST, and event-driven architectures for seamless cross-application connectivity
• Build real-time 'Live Intelligence' pipelines using Speech-to-Text (STT), Natural Language Understanding (NLU), and conversational AI systems
• Enable operators to interact with systems via voice-enabled interfaces and AI-driven conversational summaries
• Design scalable and reusable integration patterns to enable unified access across enterprise applications ('single pane of glass' architecture)
• Establish governance frameworks for Agentic AI including auditability, compliance, human-in-the-loop controls, and Agentic Level Agreements (ALA)
• Partner with data science teams to fine-tune LLMs, optimize RAG pipelines, and ensure domain-specific grounding of AI outputs
• Develop architectures that support high concurrency, low latency, and enterprise-scale resilience
• Enable real-time data ingestion from multiple sources including communication streams, enterprise applications, and monitoring systems
• Drive innovation in AI-based automation, predictive analytics, and intelligent decision systems
• Provide technical leadership and mentorship to data science and AI engineering teams