Sr Data Scientist II

Experteer Overview In this Senior Data Scientist II role, you will advance generative AI, retrieval-augmented systems, and agentic AI to power drafting and search capabilities for legal customers. You’ll own modular, production-grade Python applications and collaborate across teams to deliver reliable LLM-enabled solutions. You’ll design robust architectures, ensure observability and resilience, and drive measurable impact in a fast-paced AI-enabled legal tech environment. This is a hands-on role with significant ownership and scope to shape scalable AI products. Compensation / Benefits * Architect modular agentic applications with clear separation of retrieval, prompt construction, model invocation, tool execution, state/history management, orchestration, validation, and response formatting * Refactor complex or legacy Python code for correctness, readability, modularity, and performance * Own production readiness for AI components including input validation, error handling, timeouts, retries, fallback behavior, configuration, and credential security * Establish observability for LLM and retrieval workflows via structured logging, metrics, tracing, alerts, and actionable error reporting * Define interfaces and data contracts between retrieval, orchestration, model, and downstream components * Write comprehensive tests (unit, integration, regression, end-to-end) including failure modes and degraded scenarios * Review code for architectural and operational risks and provide production-aligned feedback * Diagnose and optimize latency, memory usage, retrieval performance, token cost, and scalability * Participate in production deployments, incident investigations, root-cause analysis, and reliability improvements * Take end-to-end ownership from design through deployment and monitoring Tasks * Advanced Python proficiency with production-grade applications * Strong fundamentals in data structures, algorithms, OOP/functional design, typing, and complexity analysis * Ability to transform prototypes into modular and observable systems * Understanding of software design principles (separation of concerns, DI, interfaces, configuration) * Experience with automated testing (pytest) including mocking external services * Experience designing resilient distributed applications with timeouts, retries, partial failures, idempotency, and graceful degradation * Production observability experience (logging, metrics, tracing, alerting, incident troubleshooting) * Ability to conduct rigorous code reviews and manage lifecycle ownership from design to operation * Understanding of production LLM concerns (structured output validation, prompt versioning, token/cost controls, security, evaluation) * Strong cross-functional delivery and communication skills Key requirements * flexible working hours * wellbeing initiatives * shared parental leave * study assistance * sabbaticals * location-based benefits

Experteer Overview In this Senior Data Scientist II role, you will advance generative AI, retrieval-augmented systems, and agentic AI to power drafting and search capabilities for legal customers. You’ll own modular, production-grade Python applications and collaborate across teams to deliver reliable LLM-enabled solutions. You’ll design robust architectures, ensure observability and resilience, and drive measurable impact in a fast-paced AI-enabled legal tech environment. This is a hands-on role with significant ownership and scope to shape scalable AI products. Compensation / Benefits * Architect modular agentic applications with clear separation of retrieval, prompt construction, model invocation, tool execution, state/history management, orchestration, validation, and response formatting * Refactor complex or legacy Python code for correctness, readability, modularity, and performance * Own production readiness for AI components including input validation, error handling, timeouts, retries, fallback behavior, configuration, and credential security * Establish observability for LLM and retrieval workflows via structured logging, metrics, tracing, alerts, and actionable error reporting * Define interfaces and data contracts between retrieval, orchestration, model, and downstream components * Write comprehensive tests (unit, integration, regression, end-to-end) including failure modes and degraded scenarios * Review code for architectural and operational risks and provide production-aligned feedback * Diagnose and optimize latency, memory usage, retrieval performance, token cost, and scalability * Participate in production deployments, incident investigations, root-cause analysis, and reliability improvements * Take end-to-end ownership from design through deployment and monitoring Tasks * Advanced Python proficiency with production-grade applications * Strong fundamentals in data structures, algorithms, OOP/functional design, typing, and complexity analysis * Ability to transform prototypes into modular and observable systems * Understanding of software design principles (separation of concerns, DI, interfaces, configuration) * Experience with automated testing (pytest) including mocking external services * Experience designing resilient distributed applications with timeouts, retries, partial failures, idempotency, and graceful degradation * Production observability experience (logging, metrics, tracing, alerting, incident troubleshooting) * Ability to conduct rigorous code reviews and manage lifecycle ownership from design to operation * Understanding of production LLM concerns (structured output validation, prompt versioning, token/cost controls, security, evaluation) * Strong cross-functional delivery and communication skills Key requirements * flexible working hours * wellbeing initiatives * shared parental leave * study assistance * sabbaticals * location-based benefits