Principal Product Manager - Conversational AI

Overview

Senior individual contributor role owning product strategy for Equinix's conversational AI and assistant platforms, spanning chat, voice, and agentic interfaces used by employees, customers, and partners.

What you'll do

• Bring working knowledge of conversational AI, dialogue systems, agent orchestration, cloud infrastructure, and enterprise data architecture to product and platform decisions.
• Partner with engineering and architecture teams to evaluate LLM architectures, conversational agent design patterns (orchestrator/worker, multi-agent handoff, tool calling), cloud deployment approaches, and enterprise data pipelines.
• Participate in technical and architecture reviews and product and roadmap discussions for the conversational platform.
• Translate technical choices, constraints, and risks into business implications leaders can act on.
• Ensure conversational AI products are designed for enterprise scale, security, reliability, multi-channel support (chat, voice, embedded assistants), and reuse across business functions.
• Guide decisions on prompt design, retrieval augmented generation, conversation flow and dialogue management, model customization, fine tuning, and model selection.
• Help teams determine when a smaller model may provide better latency, cost, or control than a larger model.
• Partner with AI and machine learning engineering teams on deployment across cloud, private infrastructure, and low-latency environments.
• Evaluate emerging approaches such as multi-agent coordination, model routing, tool/function calling, memory and context management, and hybrid model deployment.
• Use conversation quality metrics, containment and escalation rates, model performance data, evaluation results, user feedback, and business outcomes to guide product priorities.
• Define product requirements for reliability, availability, latency, performance, monitoring, usage limits, and incident response.
• Partner with engineering to improve visibility into agent behavior, model performance, cost, conversation logs, and production issues.
• Establish requirements supporting traceability, explainability, auditability, fairness, privacy, and regulatory compliance.
• Work with Legal, Security, Privacy, and AI Governance teams to incorporate policies and responsible AI requirements, including data handling within chat, voice, and memory features.
• Partner with Design to create conversational UX that explains AI use, manages expectations, and provides review, control, hand-off to a human, and approval within the conversation.
• Lead decisions on tradeoffs among business value, delivery speed, technical complexity, cost, performance, and risk.
• Establish clear, repeatable methods for evaluating major conversational AI product and architecture decisions.
• Identify risks early, including hallucination, unintended actions, and improper data exposure, and determine the appropriate level of governance and human oversight.
• Build alignment across Product, Engineering, Architecture, Legal, Information Security, Data, Design, and business functions on the conversational AI roadmap.
• Influence decisions through expertise, clear reasoning, and working relationships rather than direct authority.
• Explain complex technical topics clearly to both technical and business audiences.
• Work with senior leaders to connect conversational AI investments to business priorities, customer value, productivity, and operational outcomes.

What you'll need

• Master's degree or doctorate in Computer Science, Data Science, Statistics, Engineering, Physics, or a related field.
• Experience working with models and platforms from OpenAI, Anthropic, Google, or the open source community, including agent frameworks and orchestration tooling.
• Experience with machine learning operations, model evaluation, AI monitoring, or conversational AI observability tools.
• Experience defining service requirements for conversational AI systems, including availability, latency, performance, monitoring, usage limits, and operational support.
• Knowledge of responsible AI practices, including explainability, model documentation, evaluation, audit processes, governance, and policy implementation for conversational systems.
• Experience working with research, engineering, or innovation teams to bring conversational AI capabilities into production.
• Experience designing conversational AI user experiences that support transparency, consent, user review, and appropriate human control (e.g., escalation to a live agent).
• Experience in data centers, cloud infrastructure, telecommunications, or enterprise technology.
• Experience building AI assistants, chatbots, voice agents, or AI-enabled conversational workflows at enterprise scale.
• Experience with business software, enterprise platforms, or products designed for developers.

Details

• Location: Bangalore Office BLS2.
• This is a new position within the organization.