Principal Software Engineer – AI SRE

Harness is the AI Software Delivery Platform company, led by technologist and entrepreneur Jyoti Bansal (founder of AppDynamics, acquired by Cisco for $3.7B). Harness has raised approximately $570M in funding and is valued at $5.5B, backed by leading investors including Goldman Sachs, Menlo Ventures, IVP, Unusual Ventures, Citi Ventures, and more. As AI accelerates code creation, the real bottleneck has shifted to everything after the code – testing, deployments, application security, reliability, compliance, and cost optimization. Harness brings AI and automation to this “outer loop,” helping teams ship software faster while maintaining security and governance throughout the entire software delivery lifecycle.

Powered by Harness AI and the Software Delivery Knowledge Graph, the Harness Platform applies deep context and intelligent automation across the software delivery lifecycle with governance and policy-driven controls embedded throughout the platform.

Over the past year, Harness powered over 185M deployments, 82M builds, 18T flag evaluations, 8M security scans, 9.1B optimized tests, 3T protected API calls, and helped manage $2.8B in cloud spend — enabling customers like United Airlines, Morningstar, and Choice Hotels to accelerate releases by up to 75%, reduce cloud costs by up to 60%, and achieve 10x DevOps efficiency.

With a global team across 26 offices and 27 countries, Harness is shaping the future of AI software delivery — and we’re looking for exceptional talent to help us move even faster.

Position Summary

Harness is seeking a Principal Software Engineer to shape the architecture and direction of AI SRE. You will build scalable platforms and AI investigators that help engineering teams understand incidents, correlate evidence, identify likely causes, and determine the next action.

This role combines hands-on backend and distributed-systems expertise with organization-wide technical leadership, mentorship, and customer engagement.

About AI SRE

Harness AI SRE helps teams investigate and resolve production incidents by reasoning across deployments, source code, pull requests, alerts, telemetry, feature flags, documentation, runbooks, and previous incidents.

We are building systems that investigate, reason, and act—not simply answer questions. This requires reliable distributed systems, intelligent retrieval and agentic workflows, and experiences engineers can trust during high-pressure incidents.

Principal Engineers at Harness

Principal Engineers possess a blend of domain expertise and world-class technical leadership. They influence architecture and product strategy across teams, solve the organization’s most difficult technical problems, develop engineers, and translate ambiguous customer needs into scalable solutions.

Technical Competencies

• Strong backend, distributed systems, databases, and reliability expertise.
• Deep understanding of incident management, observability, SLOs, and RCA.
• Experience with AI/agentic systems, retrieval, and engineering data.
• Strong problem-solving and architectural judgment.
• Ability to balance technical decisions with product and customer needs.

Leadership Competencies

• Lead complex, cross-team initiatives with clear technical direction.
• Mentor engineers and raise engineering quality.
• Drive simplification, reusable platforms, and better execution.
• Make strategic decisions around risk, resources, and build-vs-buy.
• Strong communication, collaboration, and organizational impact.

Key Responsibilities

• Define architecture for incident management, on-call, reliability, and AI investigation workflows.
• Build scalable Java services, event-processing systems, data platforms, and cloud infrastructure.
• Develop AI investigators that correlate code, deployments, alerts, telemetry, and organizational knowledge.
• Drive agentic workflows, retrieval pipelines, and evidence-based reasoning.
• Coordinate initiatives across backend, AI/ML, integrations, frontend, Infrastructure, Product, and Design.
• Improve production reliability, scalability, performance, security, and observability.
• Solve complex problems involving real-time correlation, multi-tenancy, AI accuracy, and integration reliability.
• Create reusable platform capabilities and prevent duplicated engineering effort.
• Support roadmap and resource planning while responding to incidents and customer escalations.
• Mentor engineers and represent H…