the company harnesses the power of ai to transform how revenue teams win. the company revenue ai operating system unifies data, insights, and workflows into a single, trusted system that observes, guides, and acts alongside the worlds most successful revenue teams. powered by the company revenue graph, ai-powered intelligence, specialized agents, and trusted applications, the company helps more than 5,000 companies around the world deeply understand their teams and customers, automate critical sales workflows, and close more deals with less effort. for more information, visit company.
at the company, you will join a company built on innovative products, ambitious goals, and passionate people. we are shaping the future of revenue intelligence and we want people who are excited to build what comes next. you will work with a team that dreams big, moves fast, and cares deeply about the craft and about each other. here, transparency and trust are core to how we operate, and every person has the opportunity to make a visible impact. if you want to grow, stretch, and do work that truly matters, the company is the place to do the best work of your career.
as a senior backend engineer on the company's ai framework team, you will build the foundational platform that enables the entire organization to design, evaluate, deploy, and operate ai agents at scale. this is a new, high-impact team responsible for creating the frameworks, tools, and guardrails that power the company's agentic ecosystem.
youll work deeply in the agentic space, designing systems for orchestration, evaluation, observability, and safety. the platforms you build will be used by multiple teams across the company, making your impact immediate and company-wide.
youll own:
agentic framework architecture: designing and building the company's internal agentic framework, leveraging and integrating industry-standard tools such as langchain, langsmith, adk, and similar ecosystems.
evaluation and quality systems: building evaluation frameworks and workflows for ai agents, including offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
observability, monitoring, and guardrails: providing the organization with robust observability capabilities for ai agents, including tracing, logging, monitoring, cost tracking, and safety guardrails to ensure reliable and responsible usage.
Developer enablement platforms: creating apis, sdks, and abstractions that enable product teams to easily build, TEST, and operate agents while adhering to platform standards.
cross-language integrations: designing integrations and tooling across Python and JAVA to enable seamless adoption of the ai framework within the company's broader backend ecosystem.
agent runtime and execution engine: building the runtime responsible for orchestrating agent execution, managing tool calls, maintaining state and memory, and ensuring reliable execution across distributed systems.
youll solve:
agent lifecycle and orchestration complexity: managing agent execution, tool usage, memory, workflows, and failure modes in production-grade systems.
ai system reliability at scale: ensuring agents remain observable, debuggable, and safe as usage scales across teams and products.
evaluation and drift challenges: detecting quality regressions, model behavior changes, and unintended agent behaviors through robust evaluation and monitoring systems.
platform adoption friction: balancing flexibility with guardrails so teams can innovate quickly without compromising reliability, security, or cost controls.
youll impact:
company-wide ai enablement: empowering every engineering team at the company to build agent-based solutions faster, with higher quality and confidence.
foundational ai infrastructure: establishing the core frameworks, evaluations, and observability standards that all ai agents at the company will rely on.
This position is open to all candidates.