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Tier-1 brand, hybrid/remote option, and metro location increase applicant competition.
Strong observability and database-domain requirements make industry transfer moderately sensitive despite transferable backend skills.
Explicit 10+ years plus technical and managerial mandates create strict shortlisting filters.
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Lead and manage a full-stack engineering team (6–8 engineers) focused on Database Observability products, owning end-to-end delivery, system quality, and operational excellence.
Set strategic technical direction incorporating AI technologies (Agentic AI, MCP, LLMs) to advance database telemetry, diagnostics, and autonomous remediation.
Drive architecture for high-throughput, low-latency ingestion pipelines and agents, while partnering with Product and Design to execute impactful features.
10+ years total software engineering experience with at least 2 years managing engineering teams.
Strong technical background in backend and distributed systems (e.g., Go, Java, Python) and experience with high-throughput data pipelines.
Foundational knowledge of relational and NoSQL database engines and telemetry collection challenges under production loads.
Experience delivering complex multi-quarter technical initiatives on time with high quality; familiarity with CI/CD, microservices, containerization (Docker, Kubernetes), and production observability.
Experienced leader capable of coaching senior engineers with domain expertise in distributed systems and AI-driven software.
Technically fluent to engage in architectural discussions around streaming telemetry (Kafka), database agent development, and AI integration.
Proven track record managing team health, performance, and scaling in fast-paced environments involving ground-up product launches or rapid growth.