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Engineering Manager - Data Platform

Harness
CompanyHarness
CategoryEngineering
LocationBengaluru
RemoteOn-site (inferred)
EmploymentNot stated
LevelManager
SalaryNot stated by the employer
Posted24 Mar 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
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 This role comes under the AppSec Platform charter, focused on designing and developing a multi cloud, portable, OSS backed, streaming first data platform for powering API observability & security products. Additionally the team is also responsible for common services in the authentication & authorization space. The platform serves as the core-pillar for customer facing Analytics & consumption layer for various product modules like Catalog, Run-time Protection, Application/AI Security. You will be expected to manage and grow an engineering team of 8-10 engineers, driving execution, innovation, and delivery of high-impact platform capabilities, drive operational excellence through monitoring, reliability improvements, cost optimization of large-scale data systems and most importantly contribute to the company’s mission of becoming a global leader in the AppSec space. About the Role Architect and build large-scale data platforms and microservices-based systems that process and analyze high-volume API traffic. Lead project execution from planning to delivery , defining scope, milestones, and deliverables in collaboration with cross-functional teams. Ensure engineering teams follow best practices in architecture, coding standards, testing, and security . Debug and resolve complex distributed system issues across streaming, storage, and service layers. Manage engineering priorities, allocate resources effectively, and ensure timely delivery of projects . Drive technical innovation , evaluating and adopting new technologies to improve platform scalability and performance. Define and track KPIs for engineering productivity, system performance, and reliability . Collaborate closely with product managers, data scientists, and other engineering teams to build features aligned with customer and business needs.   About You 9–12 years of overall engineering experience preferably in the platform space. At least 2 years of engineering management experience. Proven ability to lead, mentor, and grow teams of 8+ engineers, fostering a high-performance engineering culture. Hands-on experience building and scaling distributed data platforms and microservices architectures. Strong programming experience in Java, Python, or Go. Operational experience with streaming and data processing technologies such as Kafka, Kafka Strea
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