The proliferation of machine log data gives organizations unprecedented real-time visibility into their infrastructure and operations. Capturing that value means solving two hard problems at once: building backend systems that can reliably ingest, manage, and process petabytes of heterogeneous, high-volume data, and building the intelligence that reasons over that data to deliver real-time insight.
This role sits at the intersection of both. Agent orchestration at our scale is a highly complex problem, involving reliability challenges that come with long-running multi-agent tasks. Similarly scaling an agent’s capabilities to solve a diverse range of tasks requires careful context engineering. It's a rare opportunity to own a production distributed system end-to-end while shaping how LLM-powered agents operate over real-world data at scale.
You'll join a small, high-impact, cross-geo team and operate with a strong bias for action: defining scope, setting milestones, and shipping incremental, well-tested improvements that directly enhance the customer experience.
What You'll Do
Design, implement, and optimize agentic AI platform—including our agent harness, proprietary tools that work over big data, orchestration layer for multi-agent long-running tasks & integrations to third party tools.
Write robust, reusable, testable & maintainable code with AI assistance.
Ensure the reliability, performance, and observability of deployed agents through rigorous evaluation, testing, monitoring and continuous improvement.
Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end, AI-powered insights.
Required Qualifications
BTech, MTech, or equivalent in Computer Science, Data Science, or a related discipline.
4–6 years of industry experience with a proven track record of ownership and delivery.
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Hunger for learning and stepping out of your comfort zone. This role is for people who are great at distributed systems, and want to pivot to working on building AI agents.
Strong communication skills and a passion for shaping emerging AI paradigms.
Demonstrated experience building backend services that handle data at large scale.
Solid grasp of the performance characteristics of commonly used data structures (maps, lists, trees, etc.) and the fundamentals of scalable system design.
Desired Qualifications
Proficiency in Python and working knowledge of LLM core concepts, prompt design, and agentic design patterns.
Prior experience building and deploying AI agents or LLM applications - as side projects or in production.
Experience using Sumo Logic or other observability products for reliability and security.
About Us
Sumo Logic, Inc. helps make the digital world secure, fast, and reliable by unifying critical security and operational data through its Intelligent Operations Platform. Built to address the increasing complexity of modern cybersecurity and cloud operations challenges, we empower digital teams to move from reaction to readiness—combining agentic AI-powered SIEM and log analytics into a single platform to detect, investigate, and resolve modern challenges. Customers around the world rely on Sumo Logic for trusted insights to protect against security threats, ensure reliability, and gain powerful insights into their digital environments. For more information, visit www.sumologic.com.
Sumo Logic Privacy Policy. Employees will be responsible for complying with applicable federal privacy laws and regulations, as well as organizational policies related to data protection.
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