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 were looking for exceptional talent to help us move even faster.

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.

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 actnot simply answer questions. This requires reliable distributed systems intelligent retrieval and agentic workflows and experiences engineers can trust during high-pressure incidents.

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

• 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.

• 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.

• 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 Harness as an AI SRE and reliability engineering expert.

• 12 years of professional software development experience.
• Deep experience building large-scale backend systems preferably in Java.
• Strong knowledge of object-oriented design algorithms concurrency transactions and distributed systems.
• Experience designing microservices and highly available production systems.
• Production ownership on-call incident response and observability experience.
• Proven ability to lead ambiguous multi-team initiatives from concept to production.
• Strong technical mentorship architectural leadership and product judgment.
• Active use of AI-assisted development tools and understanding of their strengths and limitations.

What Were Looking For

• Strong Backend Engineering Deep Java expertise distributed systems databases concurrency scalability and sound architectural decision-making.
• Production Engineering Mindset Experience owning production systems on-call/incident response troubleshooting complex issues and building strong observability and reliability.
• Technical Leadership Strong code reviews mentoring driving ambiguous initiatives and influencing architecture across teams.
• Product Thinking Customer-focused mindset challenging assumptions partnering with Product and building solutions that deliver real user value.
• AI-Native Engineering Extensive use of AI in development familiarity with coding assistants reasoning models agents and retrieval and willingness to experiment and shape AI-first engineering practices.

• Accelerating Our Mission to Bring AI to Everything After Code
• Goldman Sachs leads investment in software delivery startup Harness at $5.5 billion valuation
• How Harness runs 16 startups within a startup at scale Jyoti Bansal
• Harness Research Shows AI Visibility Crisis Fueling Security Nightmare
• Harness has been named to the Inc. Power Partner list for software delivery success

All qualified applicants will receive consideration for employment without regard to race color religion sex or national origin.

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