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Mid-level experience and Bangalore metro increase competition despite specialized LLM skillset and Series-A branding.
Applied LLM engineering skills are transferable across AI-driven companies but research-domain specifics moderate transferability.
Mandatory 4+ years, 2+ years LLM production experience, and specific tooling requirements create high shortlisting strictness.
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Own design, development, and continuous improvement of AI agent systems for market research operations.
Lead synthetic data generation, evaluation dataset creation, and automated data quality monitoring to enhance AI model performance.
Drive system architecture and scale solutions including long-context handling, cascading error mitigation, and prompt engineering strategy.
4+ years of engineering experience, with at least 2 years focused on LLM systems or applied ML in production.
Strong Python skills; experience with Go or TypeScript is a plus.
Deep hands-on experience with LLMs, synthetic data pipelines, evaluation frameworks, and production AI system optimization.
Experience building and operating production AI systems (not just prototypes).
Experienced in applied ML systems engineering with ownership over production-grade AI pipelines.
Skilled at debugging complex, non-deterministic system failures and driving problems to resolution independently.
Familiar with prompt engineering, model fine-tuning, and evaluation methodologies relevant to large language models.