> Markdown version of [/jobs/ext/1451727-conversational-ai-engineer](https://www.wearedevelopers.com/jobs/ext/1451727-conversational-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Conversational AI Engineer - **Company:** Bright Vision Technologies - **Location:** Cary, NC, United States (Remote available) - **Experience:** Expert - **Salary:** $100,000.0 - $150,000.0 - **Contract:** Permanent contract - **Skills:** Applications Architecture, Application Frameworks, Computational Linguistics, Python (Programming Language), Software Engineering, Enterprise Software Applications, Chatbots, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Indexer, Information Technology, Free and Open-Source Software - **Published:** July 26, 2026 - **Apply:** https://www.careerjet.com/jobad/us807e507d508df822e0e3100348d54a9e ## About the Role * Bachelor's or Master's degree in Computer Science, Computational Linguistics, or a related field. * Six or more years of software engineering experience, with significant time on LLM-based applications. * Demonstrated experience shipping LLM-powered products to production. * Deep familiarity with modern LLM APIs and agent frameworks. * Strong understanding of retrieval-augmented generation, embeddings, and vector databases. * Experience designing evaluation pipelines for non-deterministic systems. * Strong Python skills and comfort with modern application frameworks. * Solid grasp of responsible AI principles, including safety and policy considerations. * Excellent written and verbal communication skills. * Track record of mentoring engineers and influencing technical direction. Preferred Qualifications * Public writing, talks, or open-source contributions on LLM application development. * Experience with multi-agent architectures and complex tool-use systems. * Familiarity with fine-tuning workflows and when to choose them over prompting. * Exposure to product domains such as customer support, coding assistants, or analytics agents. * Experience integrating LLMs into enterprise software systems with strict compliance requirements. ## Description * Define organization-wide standards, patterns, and reference architectures for LLM-based applications. * Design prompt structures, instruction templates, and retrieval strategies for diverse production use cases. * Architect agentic systems incorporating tool use, planning, memory, and multi-step reasoning. * Lead the design of retrieval-augmented generation pipelines including chunking, indexing, and reranking strategies. * Develop evaluation frameworks for prompt quality, agent reliability, and end-to-end task success. * Build internal tooling and libraries that accelerate LLM application development across teams. * Establish guardrails, safety filters, and policy enforcement patterns for LLM-powered products. * Collaborate with model engineering teams on prompt-model co-design and fine-tuning opportunities. * Conduct technical reviews of LLM application designs across multiple product teams. * Mentor engineers and applied scientists on prompt engineering and LLM application architecture. * Lead red-teaming exercises and continuously improve robustness against adversarial inputs. * Track latency, cost, and quality trade-offs in LLM application design and recommend optimizations. * Document patterns, anti-patterns, and lessons learned for broad internal reuse. * Stay current with LLM capabilities, tooling, and research, and translate advances into practical guidance. ## Related Videos - [LLMs in the wild: Building an AI agent that survives production](https://www.wearedevelopers.com/videos/100319-llms-in-the-wild-building-an-ai-agent-that-survives-production) - [Designing and Deploying Distributed Multimodal Multi-Agent Systems with Google's AI Stac](https://www.wearedevelopers.com/videos/1976-designing-and-deploying-distributed-multimodal-multi-agent-systems-with-google-s-ai-stac) - [Optimizing Discovery: PostgreSQL's Role in Transforming GetYourGuide's Search](https://www.wearedevelopers.com/videos/1647-optimizing-discovery-postgresql-s-role-in-transforming-getyourguide-s-search) - [Chatbots are going to destroy infrastructures and your cloud bills](https://www.wearedevelopers.com/videos/1130-chatbots-are-going-to-destroy-infrastructures-and-your-cloud-bills) - [Give Your LLMs a Left Brain](https://www.wearedevelopers.com/videos/1160-give-your-llms-a-left-brain) - [Dynamic Entities in .NET: Building Low-Code Systems on Top of Entity Framework Core](https://www.wearedevelopers.com/videos/100218-dynamic-entities-in-net-building-low-code-systems-on-top-of-entity-framework-core) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [13 AI Tools You Have to Try](https://www.wearedevelopers.com/magazine/219-13-ai-tools-you-have-to-try) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [The Prompt Engineer ✍️](https://www.wearedevelopers.com/magazine/216-the-prompt-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Tell if Something Was Written by ChatGPT](https://www.wearedevelopers.com/magazine/314-how-to-tell-if-something-was-written-by-chatgpt)