Product Manager

About Giga

Giga is building AI agents that aim to automate 98% of enterprise support tickets and operations workflows. We deploy self-improving, emotionally intelligent agents that handle millions of customer interactions across voice, chat, and email for Fortune 100 enterprises like DoorDash.

Our agents don't just respond—they continuously learn and improve, automatically increasing resolution rates from 60% to 98% through pattern recognition and policy refinement. They orchestrate complex multi-party workflows in real-time: simultaneously coordinating between customers, delivery drivers, and internal systems while cross-referencing policies and databases—all in under 500 milliseconds.

Role Overview

We're looking for a Product Manager to help us achieve our goal of automating 98% of enterprise support and operations workflows. You'll own critical parts of our AI agent platform—building the products that enable self-improving agents to handle increasingly complex scenarios without human intervention.

You'll work at the intersection of cutting-edge AI capabilities and enterprise-grade product development: defining how agents learn from every interaction, orchestrating multi-party workflows across voice and chat, and expanding our platform into regulated industries like healthcare and financial services.

This role requires someone who can think deeply about AI product strategy while also diving into the technical details of real-time orchestration, emotional intelligence, and enterprise compliance.

What You'll Own

Self-Improving Agent Platform

• Drive the product strategy for agents that automatically improve from 60% to 98% resolution

• Define how agents learn from every interaction—pattern recognition, policy refinement, edge case handling

• Build feedback loops that identify gaps and automatically expand agent capabilities

• Own the path from "agent handles simple cases" to "agent handles 98% of all cases"

Multi-Party Orchestration

• Lead product strategy for complex real-time workflows (e.g., coordinating customer, driver, and merchant simultaneously)

• Define how agents make decisions by cross-referencing multiple data sources, policies, and external systems in real-time

• Own the sub-500ms latency experience across voice, chat, and email channels

• Drive emotional intelligence features—sentiment detection, tone matching, natural conversation flow

Agent Builder & Console

• Define the product vision for our no-code/low-code agent configuration platform

• Own the policy engine, scenario builder, and custom code execution capabilities

• Drive improvements to knowledge base management and RAG integrations

• Shape the developer experience for teams building and customizing agents

Expansion into Regulated Industries

• Partner with healthcare, financial services, and compliance-heavy customers to understand their unique requirements

• Define product capabilities for high-compliance environments (audit trails, data privacy, regulatory adherence)

• Own integrations strategy (Zendesk, Salesforce, industry-specific systems)

• Drive the 2-week enterprise deployment goal that differentiates us from competitors

Key Responsibilities

Product Strategy & Execution

• Define and execute the roadmap toward 98% automation of support tickets and operations workflows

• Make hard prioritization decisions: which agent capabilities unlock the next 10% of automated resolution?

• Ship features that directly move resolution rates from 90% toward 98%

• Translate the "enterprise operations platform" vision into concrete milestones across support, compliance, and operations

Technical Product Leadership

• Understand and communicate complex real-time systems (sub-500ms latency requirements)

• Work closely with engineering on architecture decisions and technical tradeoffs

• Evaluate AI model capabilities and translate them into product features

• Drive API design and developer experience for headless agents and integrations

Customer Partnership

• Build deep relationships with Fortune 100 customers to understand why the last 10% of tickets still need humans

• Translate customer feedback into agent capabilities that close the gap toward 98% automation

• Monitor resolution rates, identify failure patterns, and drive systematic improvements

• Partner with customers in healthcare and finance to define compliance-grade automation

Cross-Functional Collaboration

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