This skill helps you design and implement robust LLM applications by applying production-ready patterns for RAG, agents, prompts, and observability.
Find, trial, compare, and govern AI agents before hiring
Engineering
Build, review, ship, and maintain software systems with agent assistance.
What team job or business role does the user need filled?
Start from a plain-language department or occupational family, then open related technical categories or job-matcher prompts.
- department or team-role discovery
- plain-language job briefs
- business outcome shortlists
- non-technical browsing
Start from user language
- Review a repository and suggest the safest first automation.
- Ship a frontend change with code review and a sandbox trial.
Sandbox-first next steps
Engineering candidates
Showing 12 of 5000. Adjust filters to narrow the review list without losing job context.
You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph.
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This skill guides and implements production-grade LangChain LangGraph agents using async patterns, best practices, and observability for scalable AI systems.
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Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.
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This skill enables LLM function calling to execute external tools and return structured results for seamless integrations.
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This skill provides production-ready LLM integration patterns for function calling, streaming, local inference, and fine-tuning to streamline tool use.
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Evaluating LLMs as Agents
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Ultrafast Lifelike AI Speech
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LMQL is a programming language for LLMs.
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This skill helps agents securely obtain anonymous email via LNemail for 2FA, notifications, and messages using Lightning payments.
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LobeChat Cloud offers 450,000 free computing credits to registered users, with no complex configuration required, ready-to-use features, unlimited conversati…
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LobeChat: Personal LLM productivity tool, surpassing the ChatGPT / OLLaMA user experience
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Role-family pages stay focused on plain-language job review; complete review records and finalist profile resources stay linked here.
Supporting review linksLinks, review order, and page-specific notes remain available here.
5000 candidates for Engineering. Open matching profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
- 01Site contextShared review rules
- 02Role familyOpen the focused review record
- 03Profile pageOpen the candidate page
- 04Profile resourcesEvidence, setup, trust, trial, and history files
Use the links and review path below for role-family candidates, job brief context, and finalist profile resources before action.