Staff Engineer - TE

Thoughtspot

10 - 15 years

30 - 35 Lacs

bengaluru

Posted:1 week ago| Platform:

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Skills Required

computer science c++ orchestration coding machine learning technical leadership system design distribution system analytics python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Build and Manage AI Platform: Architect and implement a robust AI platform, including LLM gateways and infrastructure for AI agents capable of orchestrating complex workflows and conversational interfaces.
Model Orchestration: Develop capabilities to dynamically configure and switch between specialized models optimized for different tasks such as reasoning, thinking, and coding to ensure optimal performance and cost-efficiency.
Advanced Observability: Design and build comprehensive observability solutions using the latest frameworks (such as Langfuse) to provide deep visibility into agent performance, traces, and interactions.
Benchmarking & Evaluation: Build rigorous benchmarking frameworks for AI applications to systematically evaluate model performance, latency, and quality across various use cases.
Accuracy & Drift Monitoring: Design and implement data pipelines to collect production data and assess drifts in the accuracy of AI applications, ensuring high reliability and trust in our AI agents.
System Scale & Reliability: Design, develop, test, maintain, monitor, and improve distributed systems and platform infrastructure to enable high-velocity iteration.
Technical Leadership: Bring technical thought leadership to advance ThoughtSpot s differentiation and market leadership in democratizing data analytics for business users.

Required skills and qualifications

Education : Masters/PhD degree in Computer Science, Machine Learning, Data Science, or a related field.
Experience : Have 10+ years of experience designing and implementing consumer-grade AI applications or distributed platforms. You understand what it takes to write software that is used by millions of people.
AI Platforms & Agents: Proven track record of building AI platforms, specifically LLM gateways, and experience with agentic architectures (e.g., LangChain, AutoGPT concepts, or custom orchestrators).
Observability : Hands-on experience with modern AI observability stacks (e.g., Langfuse, Arize, or custom solutions) for monitoring LLM behavior in production.
Evaluation Frameworks : Experience building and maintaining benchmarking frameworks to evaluate the quality and performance of Generative AI applications.
Data Engineering : Ability to build data pipelines for logging, evaluation datasets, and drift detection.
Coding Proficiency : Strong coding skills in one of the modern languages such as C++, Go, Java, or Python.
System Design : Experience with complex, high-volume distributed systems and an understanding of how to scale AI/ML infrastructure.

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