Principal Product Manager - Conversational AI

Equinix · Bangalore Office BLS2

Who are we?

Equinix is the world’s digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet.

A place where bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future.

A career at Equinix means being at the center of shaping what comes next and amplifying customer value through innovation and impact. You’ll work across teams, influence key decisions, and help shape the path forward. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work.

Job Summary

This is a senior individual contributor role with broad influence across the company. You will own the product strategy for Equinix's conversational AI and assistant platforms — chat, voice, and agentic interfaces that employees, customers, and partners interact with directly. You will work closely with engineering and architecture teams on technical decisions while also helping executives understand business implications, investment choices, and risk.

You will serve as a conversational AI product leader across Go to Market, Operations, Product, and Corporate functions. Depending on the initiative, you may advise business leaders, partner with product and engineering teams, or directly lead product strategy and delivery for conversational experiences and the platform capabilities that power them.

The conversational AI market is changing quickly — from single-turn chatbots to multi-agent, tool-using assistants. An important part of this role is evaluating new conversational AI technologies, identifying which capabilities are relevant to Equinix, and translating them into practical product and platform investment decisions.

Responsibilities

Conversational AI, Cloud, and Data Architecture

Bring strong 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 large language model architectures, conversational agent design patterns (orchestrator/worker, multi-agent handoff, tool calling), cloud deployment approaches, and enterprise data pipelines
Participate meaningfully in technical and architecture reviews, as well as product and roadmap discussions for the conversational platform
Translate technical choices, constraints, and risks into clear business implications that leaders can understand and act on
Help ensure conversational AI products are designed for enterprise scale, security, reliability, multi-channel support (chat, voice, embedded assistants), and reuse across business functions

Conversation Design, Model Strategy, and Deployment

Guide decisions on prompt design, retrieval augmented generation, conversation flow and dialogue management, model customization, fine tuning, and model selection for conversational use cases
Help teams determine when a smaller model may provide better latency, cost, or control for real-time conversational interactions than a larger model
Partner with AI and machine learning engineering teams on deployment approaches for conversational agents 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 for conversational systems
Use conversation quality metrics, containment and escalation rates, model performance data, evaluation results, user feedback, and business outcomes to guide product priorities

Platform Reliability and Responsible AI

Define product requirements for conversational AI system reliability, availability, latency, performance, monitoring, usage limits, and incident response
Partner with engineering teams to improve visibility into conversational agent behavior, model performance, cost, conversation logs, and production issues
Establish requirements that support traceability, explainability, auditability, fairness, privacy, and regulatory compliance across conversational interactions
Work with Legal, Security, Privacy, and AI Governance teams to incorporate company policies and responsible AI requirements into conversational products and platforms, including data handling within chat, voice, and memory features
Partner with Design to create clear conversational UX that explains how AI is being used, manages user expectations, and provides appropriate review, control, hand-off to a human, and approval within the conversation itself

Product Decisions and Risk Management

Lead decisions involving tradeoffs among business value, delivery speed, technical complexity, cost, performance, and risk for conversational AI features
Establish clear and repeatable methods for evaluating major conversational AI product and architecture decisions
Help teams identify risks early — including hallucination, unintended actions, and improper data exposure in conversational contexts — and determine the appropriate level of governance and human oversight
Balance the need to deliver conversational value quickly with the requirements of security, reliability, and responsible AI

Executive and Cross Functional Leadership

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 strong working relationships rather than direct authority
Explain complex technical topics in clear language that is relevant to both technical and business audiences
Work with senior leaders to connect conversational AI investments to business priorities, customer value, productivity, and operational outcomes
Develop trusted relationships so that teams engage early when evaluating important conversational AI opportunities or decisions

Qualifications

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

Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you are a qualified candidate and need assistance or an accommodation, please let us know by completing this form.

Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law.

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