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ManagerFull-timePythonJavaAWSGCPAzureMicroservicesCI/CDGoAIAPI
Salary Range
$32,640 - $44,160 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for an Engineering Manager to join our AI team at Harness, a company building the industry’s leading AI-powered software delivery platform. This role involves leading a small, high-impact team while remaining deeply hands-on, owning critical systems end-to-end, and contributing directly to design and implementation.
Key Responsibilities
- →Own delivery and technical execution for production-grade AI agents and platform capabilities.
- →Lead by example through hands-on contribution, technical decision-making, and strong engineering practices.
- →Run rapid build–measure–learn cycles, encouraging experimentation, fast feedback, and iterative improvement.
- →Translate product ideas into working systems with measurable customer impact.
- →Establish lightweight processes that enable speed, quality, and accountability without slowing teams down.
- →Partner closely with the product to shape scope, sequencing, trade-offs, and investment decisions.
Requirements
- ✓8+ years of software engineering experience with strong system design fundamentals and hands-on delivery in production environments.
- ✓1-3 years of engineering leadership or technical lead experience in fast-paced product environments.
- ✓Demonstrated ability to own and ship production systems end-to-end, from problem definition to rollout and iteration.
- ✓Working knowledge of AI-powered systems, model integration, data pipelines, or agent-based systems.
- ✓Demonstrated ability to prototype, experiment, and iterate quickly in ambiguous problem spaces.
- ✓Strong hands-on experience with distributed systems, cloud-native services, microservices, and APIs (REST/gRPC).
- ✓Proficiency in at least one mainstream programming language (Java, Python, Go, or equivalent).
- ✓Experience with CI/CD, automation, and cloud platforms (AWS/GCP/Azure).
- ✓Strong understanding of observability, reliability, and operational excellence.
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