AI-LLM Systems Engineer

🔥 2 minutes ago

🇺🇸 United States – Remote

💵 $2k - $3k / month

⏰ Full Time

🟡 Mid-level

🟠 Senior

⚙️ Systems Engineer

👻 Ghost score 0%

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Jack Westin

WebsiteLinkedInAll Job Openings

51 - 200 employees

📚 Education

👥 B2C

Education • B2C

Jack Westin is an education company focused on LSAT test preparation. It offers online courses, daily problem explanations, practice materials, and live/recorded lessons and tutoring aimed at law-school applicants seeking to improve their LSAT scores. The company operates primarily as a consumer-facing online education provider.

📋 Description

• Design, build, and maintain end-to-end AI-powered product experiences • Develop backend services, APIs, and platform integrations supporting Jack • Integrate LLMs, retrieval systems, embeddings, vector databases, tool calling, and agentic workflows where appropriate • Evaluate architectural approaches for RAG, contextual grounding, personalization, model routing, caching, and tool use • Build reliable mechanisms for passing learner, question, content, and platform context to AI systems • Collaborate with Product to assess feasibility, technical risk, cost, latency, and expected product value before development • Implement observability and monitoring for AI workflows, including failures, latency, token usage, and cost • Support experimentation across models, prompts, retrieval strategies, and orchestration approaches • Contribute to AI evaluation and regression-testing infrastructure • Design systems that are scalable, secure, maintainable, and privacy-conscious • Work closely with frontend, platform, data, QA, and instructional teams

🎯 Requirements

• Strong professional experience in full-stack or backend software engineering • Strong experience designing and working with APIs and distributed services • Production experience building applications using LLM APIs • Understanding of prompting, RAG, embeddings, semantic search, retrieval, tool calling, and agent workflows • Familiarity with model evaluation, observability, latency optimization, and inference-cost trade-offs • Ability to reason about AI system failure modes and non-deterministic behavior • Strong product mindset and ability to work effectively with incomplete requirements and ambiguity • Ability to challenge assumptions, propose alternatives, and participate in product and technical discovery • Experience with EdTech or adaptive learning products (nice to have) • Experience with personalization or recommendation systems (nice to have) • Experience with multimodal AI (nice to have) • Experience building AI evaluation pipelines (nice to have) • Familiarity with learner data, content-management systems, or educational platforms (nice to have)

🏖️ Benefits

• 100% remote • Full-time position • Real ownership and impact