Data Scientist, AI/LLM
Binance
Python
Senior Software Engineer – Applied AI
CrowdStrike
full-time
Posted on:
Origin: • 🇺🇸 United States • California, District of Columbia, Massachusetts, Virginia
Visit company websiteSalary
💰 $140,000 - $215,000 per year
Job Level
Senior
Tech Stack
GoJavaScriptPythonReact
About the role
- Build and ship LLM-powered systems that reduce toil, accelerate remediation, and improve decision-making in operations contexts
- Design and maintain evaluation frameworks: hallucination tests, regression harnesses, benchmarks, and quality gates for safe rollout
- Develop retrieval-augmented pipelines (RAG) and data strategies for grounding on logs, telemetry, runbooks, and system metadata
- Engineer AI copilots and natural-language interfaces to interact with operational data and workflows
- Create frameworks for large-scale automation such as safe code migration and transformation pipelines
- Apply adaptive AI techniques to optimize system configurations, predict anomalies, and recommend preventive actions
- Partner across teams — collaborate with AI Platform (inference/serving), SRE/Infra/Data Service/DC (operational context), and Security (safe usage)
- Implement guardrails and safety systems: prompt injection defenses, PII filtering, constrained decoding, and model observability
- Build developer-facing SDKs and APIs in Python/Go and intuitive UIs in JavaScript/React for human-in-the-loop workflows
- Leverage modern orchestration frameworks (LangChain, LangGraph, MCP, semantic routers) to coordinate multi-step, tool-augmented workflows
Requirements
- Proven experience shipping LLM-based systems into production with measurable impact
- Expertise in evaluation and testing of LLMs (benchmarks, hallucination/regression tests, grounding metrics)
- Strong programming skills in Python and Go
- Hands-on experience with LLM orchestration frameworks: LangChain, LangGraph, MCP, agent frameworks, or equivalent
- Deep understanding of RAG pipelines: embeddings, retrieval quality metrics, re-ranking, and grounding precision/recall
- Ability to translate ambiguous operational problems into AI-first solutions with clear KPIs
- Experience with evaluation frameworks: hallucination tests, regression harnesses, benchmarks, and quality gates
- Experience developing retrieval-augmented pipelines and data strategies for grounding on logs, telemetry, runbooks, and system metadata
- Experience engineering AI copilots and natural-language interfaces
- Experience implementing guardrails and safety systems: prompt injection defenses, PII filtering, constrained decoding, and model observability
- Experience building developer-facing SDKs and APIs in Python/Go and UIs in JavaScript/React (preferred)
- Bonus: experience with fine-tuning/adapters (LoRA, QLoRA, continual learning) and safety tuning
- Bonus: exposure to inference optimization and serving, latency, scaling, and resilience
- Bonus: experience building AI copilots/assistants for engineers
- Bonus: knowledge of reinforcement learning, adaptive systems, or optimization methods
- Willingness to periodically undergo and pass additional background and fingerprint check(s) consistent with government customer requirements
