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# AI Engineer

- **Company:** ONE STOP COLLECTIBLE CORP
- **Location:** Boston, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Cloud Computing, Databases, Python (Programming Language), Cloud Services, Software Safety, Software Engineering, TypeScript, Large Language Models, Multi-Agent Systems, Caching, Backend, Information Technology, Enterprise Integration, Api Design, Automation Anywhere, Api Management
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/senior-ai-engineer-seven-ai-8146005

## About the Role

* Experienced in building real LLM applications - you've shipped systems that use large models meaningfully.
 * Strong software engineering skills - Python/TypeScript, API design, backend integration, and cloud deployment.
 * Tool fluency - comfortable with RAG, vector databases (e.g., Pinecone/Weaviate), workflow frameworks (LangChain, Dust), and related tooling.
 * Architectural thinker - you can diagram end-to-end solutions incorporating context windows, caching strategies, tool calls, and multi-step reasoning.
 * Product-oriented - you care not just that the AI works, but that it delivers value safely and reliably to users., * 6+ years of software engineering experience, with at least 1+ year working building AI in production.
 * BS Degree in Computer Science or related field. Masters degree is a plus.
 * Demonstrated use of LLMs in production workflows or complex prototypes.
 * Strong coding ability in Python or equivalent; familiarity with backend frameworks and cloud services.
 * Experience with API integrations, database systems, and scalable architectures.
 * Experience with multi-modal models or multi-agent system design.
 * Familiarity with AI safety guardrails, hallucination mitigation, and structured output enforcement.
 * Knowledge of vector DBs, RAG architectures, and prompt lifecycle tooling.

## Description

* Architect and build LLM-powered systems - design retrieval workflows, context management, agent prompts, and structured output pipelines.
 * Orchestrate AI workflows using tools like LangChain, LlamaIndex, or similar frameworks, integrating them with product APIs and backend services.
 * Drive prompt engineering and iteration - refine prompts, templates, and context strategies to meet product quality and reliability goals.
 * Manage real-world evaluation metrics - measure usefulness, factual correctness, latency, and UX impact vs. classic accuracy alone.
 * Collaborate across functions - work closely with product, platform, and backend teams to ensure seamless integration.
 * Develop reliable, scalable deployments - focus on performance, cost efficiency, and observability in production environments.


## Related Videos

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- [One AI API to Power Them All](https://www.wearedevelopers.com/videos/1601-one-ai-api-to-power-them-all)
- [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean)
- [Three years of putting LLMs into Software - Lessons learned](https://www.wearedevelopers.com/videos/1508-three-years-of-putting-llms-into-software-lessons-learned)

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