Atomicwork Taps Amazon, ServiceNow AI Vet to Lead "AI-Native" Charge

SAN FRANCISCO, CA – January 08, 2026 – In a significant move signaling its aggressive push to redefine enterprise service management, AI-native platform Atomicwork today announced the appointment of Jeegar Shah as its Head of Applied AI and Platform. Shah, a seasoned leader with deep experience building production-scale AI systems at Amazon and ServiceNow, will spearhead Atomicwork’s efforts to advance its agentic AI capabilities, positioning the well-funded startup for a direct challenge against established market leaders.

The appointment comes as the IT Service Management (ITSM) and Enterprise Service Management (ESM) sectors are undergoing a radical transformation, driven by advancements in artificial intelligence. Atomicwork, founded in 2022, is betting its future on an "AI-native" strategy, a philosophy that differentiates it from incumbents who are retrofitting AI functionalities onto legacy, ticket-centric architectures.

The "AI-Native" Gambit in a Crowded Market

Atomicwork's core thesis is that true AI transformation in the enterprise cannot be achieved by "bolting on" AI to outdated systems. Instead, it requires a foundational architecture designed from the ground up to be agentic—enabling AI to reason, act, and continuously improve. This approach has attracted significant investor confidence, with the company securing a total of $40.3 million in funding, including a pivotal $25 million Series A round in January 2025 co-led by Khosla Ventures and Z47.

This war chest is critical as Atomicwork squares off against giants like ServiceNow and Atlassian. ServiceNow, a recognized market leader, has heavily integrated AI into its Now Platform, utilizing a suite of large language models and native tools called Now Assist to automate tasks and provide predictive insights. Similarly, Atlassian's Jira Service Management leverages "Atlassian Intelligence" to power virtual agents and generate AI summaries.

While these competitors promote powerful "AI-enabled" features, Atomicwork’s CEO and co-founder, Vijay Rayapati, frames the distinction clearly. "At Atomicwork, we're building AI that does real work for enterprises, not AI bolted onto legacy systems," he stated. The hiring of Shah is a direct reinforcement of this vision, bringing in a leader whose entire career has been focused on making AI perform reliably in complex, large-scale production environments.

A Veteran of AI's Front Lines Joins the Fray

Jeegar Shah’s resume reads like a blueprint for building modern, enterprise-grade AI. His appointment is not merely a personnel change but a strategic acquisition of top-tier expertise. Before joining Atomicwork, Shah spent over four years on Amazon's highly secretive Artificial General Intelligence (AGI) team. There, he was an engineering leader responsible for the critical pipelines for large language model training, evaluation, and release. His work was instrumental in supporting some of Amazon’s most ambitious AI projects, including early foundation models and the natural language understanding infrastructure that underpins the Alexa AI ecosystem.

Following his tenure at Amazon, Shah moved to ServiceNow, where he led enterprise AI and data science efforts. In this role, he focused on operationalizing the very kind of agentic, context-driven systems that are central to Atomicwork’s mission. He advanced multi-agent orchestration and retrieval architectures, tackling the real-world challenges of deploying sophisticated AI within large enterprises.

"Jeegar has spent his career building AI that performs in production at scale," said Rayapati. "His experience is a strong fit as we continue to advance our AI-native service management platform."

Shah’s influence also extends beyond his corporate roles. He serves on the Customer Advisory Board for LangChain, one of the most popular developer platforms for building applications with large language models. This position gives him a unique vantage point on the practical challenges and opportunities of enterprise adoption of agentic AI, providing real-world integration experience that will now directly benefit Atomicwork’s platform development.

Redefining Service Management with Agentic AI

The industry is rapidly moving beyond simple AI-powered chatbots and ticket summarization. The next frontier is agentic AI—intelligent systems that can autonomously handle multi-step tasks, interact with other systems, and learn from outcomes. This shift is validated by industry analysts, with Gartner recently launching its first Magic Quadrant dedicated to AI applications in ITSM, signaling the technology's maturity and market importance.

Atomicwork aims to be at the forefront of this evolution. Its platform is designed to eliminate the repetitive, manual work that bogs down IT, HR, and other service teams. Instead of just suggesting answers, its AI agent, "Atom," can automate entire workflows, from submitting service requests to accessing knowledge bases across disparate systems like SharePoint and Confluence, all within the flow of work in collaboration tools like Slack and Microsoft Teams.

In his new role, Shah will oversee the development of this platform, with a mandate to focus on the pillars of enterprise trust: scalability, security, governance, and operational reliability. "Atomicwork is addressing a foundational problem in enterprise software: enabling service teams to move beyond manual work through AI that performs reliably at scale," Shah commented on his appointment. "I'm excited to help build trusted AI platforms and to contribute to a team reshaping service management for a new generation of enterprises."

From Theory to Practice: Proving the AI-Native Advantage

While the vision is compelling, Atomicwork is already delivering tangible results that substantiate its "AI-native" claims. A growing list of customers report significant improvements after migrating from established competitors, citing the platform's modern architecture and deeply integrated AI as key differentiators.

For instance, Zuora, a leading monetization platform provider, switched from Jira Service Management to provide employees with instant support and automated workflows directly within Slack, leading to faster resolutions. Similarly, David Williamson, CIO at Abzena, noted that after switching from ServiceNow, Atomicwork’s agentic AI allowed his team to operate at the "speed of business," a level of agility he felt was missing from legacy systems.

The financial impact is also becoming clear. Chad Ghosn, Global CIO and CTO at Ammex, reported an "incredible" return on investment after replacing Freshworks. He noted that Atomicwork allowed his company to maintain its IT service team without adding headcount for six months while handling queries for multiple departments. Another customer, Ryder Hampton, Head of Technology at their firm, successfully deployed Atomicwork and replaced three incumbent solutions in just six weeks, achieving significant improvements in ticket deflection and a reduction in the total cost of ownership. These testimonials underscore a consistent theme: Atomicwork's AI is not just a feature but a core driver of efficiency, cost savings, and an enhanced employee experience, validating its strategy to build a service management platform for the modern, AI-powered enterprise.