Senior Technical PM, Applied AI

Job not on LinkedIn

🔥 5 minutes ago

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🤖 Artificial Intelligence

👻 Ghost score 15%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Netomi

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

📦 Logistics

📣 Marketing

💰 $30M Series B on 2021-11

Consulting • Logistics • Marketing

Netomi is a company that specializes in providing AI-powered customer experience solutions. Their platform, known as Agentic OS, is designed for enterprise-scale customer service and integrates seamlessly with existing business systems. Netomi's solutions leverage generative AI and large language models to automate over 80% of customer inquiries, enhance customer satisfaction, and reduce support costs. Netomi is trusted by global brands across various industries, offering secure, proactive, and predictive customer care through omnichannel support, including email, chat, messaging, SMS, social media, search, and voice. The company ensures compliance with stringent security standards and data protection regulations.

📋 Description

• Own the product strategy and multi-quarter roadmap for the Agents platform • Tie roadmap decisions to measurable business outcomes such as autonomous resolution rate, cost per resolution, CSAT, revenue expansion and competitive wins • Work directly with enterprise customers, Customer Success, Delivery and Sales to identify high-value problems • Translate customer needs into problem statements, PRDs, user stories, success metrics and dependency maps • Drive alignment across engineering, research, data science, QA and go-to-market teams on scope, dependencies and launch readiness • Run quarterly roadmap inputs, monthly scope locks, weekly execution reviews and launch readiness sign-offs • Own launch checklists, instrumentation, enablement and success criteria; track adoption and publish monthly Agent Outcomes readouts • Run monitoring windows and post-incident reviews and feed learnings into the roadmap • Own agent reasoning and orchestration, tool and API use, memory and context, human-in-the-loop workflows and enterprise governance • Work with AI labs and model providers to test new models and capabilities and provide evidence-based feedback • Build experiments, prototypes and agents connected to real systems through APIs and MCP tools • Run offline tests, shadow-mode testing and canary releases with clear decision criteria • Define Agent Readiness Scorecard and Go/No-Go criteria; design evaluations for task completion, tool success, policy compliance, latency and cost • Debug production agent failures, identify root causes and ensure serious failures receive fixes and regression tests • Inform model selection and routing decisions using quality, latency and cost data

🎯 Requirements

• Roughly 4–8 years of relevant experience, ideally from a deeply technical product role, applied AI engineering or research engineering with clear product ownership • Proven ownership of a complex technical product area, with features delivered to enterprise customers and measurable business results • Strong product judgment and ability to prioritize, work with customers and get capabilities shipped • Customer-first approach and ability to turn enterprise needs into clear, actionable requirements • Excellent communication skills to align engineering, research and go-to-market teams and present clearly to executives • Comfortable vibe coding, building agents, connecting APIs and MCP tools, designing evaluations and debugging production failures • Deep understanding of LLM reasoning, tool calling, multi-step task execution, orchestration patterns, evaluation methods and production observability for agents • Technical fluency with APIs, cloud environments and AI deployment workflows • Experience shipping AI agent products at a conversational AI or enterprise AI platform company is nice to have • Direct experience working with AI labs or model providers is nice to have • Familiarity with agent frameworks and protocols such as LangGraph and MCP, and with voice AI is nice to have • Experience in regulated or mission-critical industries and with large SI partners is nice to have • Public work such as a repo, demo, blog post or talk is nice to have

🏖️ Benefits

• Full-time employment • Equal opportunity employer committed to diversity in the workplace