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Mid-level generalist backend role at a high-profile AI startup in Bangalore increases applicant competition.
Core backend and data infrastructure skills transfer across industries, but LLM/evals expertise slightly increases domain specificity.
Explicit 4+ years requirement plus mandatory backend, distributed systems, and language skills increases screening strictness.
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Own and build scalable backend systems and evaluation pipelines to measure AI assistant and agent quality across real and synthetic workflows.
Develop infrastructure for evaluating frontier and open-source AI model releases to identify regressions, tradeoffs, and launch readiness.
Create and maintain agent observability systems including trace enrichment, telemetry pipelines, dashboards, and debugging workflows to improve AI behavior transparency.
Minimum 4 years experience in software engineering focusing on backend systems, distributed systems, infrastructure, or data platforms.
Strong programming skills in Go, Python, Java, C++, or similar languages emphasizing reliability, scalability, and testing.
Experience with distributed data pipelines, cloud-native infrastructure, and production observability systems.
Must be located in Bangalore, India and able to work in person.
Experienced in building reliable, scalable distributed systems with attention to product quality and AI evaluation contexts.
Comfortable working cross-functionally with product, ML, and infrastructure teams to integrate evaluation results into product improvements.
Analytically rigorous with a focus on real user experience metrics rather than superficial dashboard indicators.