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# LLM Developer

- **Company:** CAMPAIGNS & ELECTIONS MAGAZINE
- **Location:** Manhattan, KS, United States
- **Experience:** Experienced
- **Salary:** $150,000.0 - $220,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Python (Programming Language), Performance Tuning, Large Language Models, Prompt Engineering, Backend, AI Platforms, Low Latency, Machine Learning Operations, Api Design, GPT
- **Published:** June 2, 2026
- **Apply:** https://campaignsandelections.com/jobs/llm-developer/

## About the Role

* 3+ years experience building LLM or AI systems in production
 * Strong experience with RAG systems and prompt engineering
 * Proficiency in Python and LLM frameworks (LangChain, LlamaIndex, or similar)
 * Strong understanding of transformer architectures
 * Experience with vector databases and embeddings pipelines
 * Experience building APIs or backend systems for AI services
 * Experience with evaluation and monitoring of ML systems, * Experience with real-time or low-latency LLM systems
 * Background in speech + multimodal AI systems
 * Experience with agentic workflows and tool-use LLMs
 * Familiarity with model compression and optimization
 * Experience with LLM safety, guardrails, and adversarial testing
 * Contributions to open-source AI or LLM projects
 * Startup or early-stage company experience, * Optional: GitHub, portfolio, or technical writing samples

## Description

As an LLM Developer, you will own the full lifecycle of LLM-powered systems - from model selection and prompt design to inference optimization and production deployment.

You will work on systems that must be fast, accurate, and context-aware in real time. Your work directly impacts user experience during live interviews.

You are expected to think deeply about model behavior, latency, cost, and output quality - and continuously improve all four., * Implement streaming responses, caching, and batching strategies

 * Improve token efficiency and context window management
 * Reduce cost through model routing and optimization techniques

Fine-Tuning & Model Customization

 * Fine-tune models for domain-specific use cases
 * Build and manage training datasets and evaluation pipelines
 * Apply techniques such as LoRA, QLoRA, and RLHF
 * Run experiments to compare model performance across configurations

Prompt Engineering & Quality Systems

 * Design system prompts and instruction architectures
 * Build evaluation frameworks for hallucination, accuracy, and relevance
 * Perform root-cause analysis of model failures
 * Continuously iterate on prompt and retrieval strategies

Evaluation & Monitoring

 * Build LLM evaluation pipelines and benchmarks
 * Monitor production metrics including latency, quality, and cost
 * Detect model drift and regressions
 * Optimize token usage and API efficiency

Safety & Reliability

 * Implement guardrails against prompt injection and unsafe outputs
 * Test adversarial inputs and edge cases
 * Ensure privacy-first handling of user data
 * Improve robustness of real-time AI responses


## Related Videos

- [API Design - Getting Started](https://www.wearedevelopers.com/videos/33-api-design-getting-started)
- [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension)
- [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock)
- [Give Your LLMs a Left Brain](https://www.wearedevelopers.com/videos/1160-give-your-llms-a-left-brain)
- [Rest API Antipatterns](https://www.wearedevelopers.com/videos/100208-rest-api-antipatterns)
- [Speak, Code, Deploy: Transforming Developer Experience with Voice Commands](https://www.wearedevelopers.com/videos/1159-speak-code-deploy-transforming-developer-experience-with-voice-commands)

## Related Articles

- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [Who Owns Your Content in the Age of LLMs?](https://www.wearedevelopers.com/magazine/610-who-owns-your-content-in-the-age-of-llms)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [Dev Digest 196: AI Killed DevOps, LLM Political Bias & AI Security](https://www.wearedevelopers.com/magazine/659-dev-digest-196-ai-killed-devops-llm-political-bias-ai-security)
- [13 AI Tools You Have to Try](https://www.wearedevelopers.com/magazine/219-13-ai-tools-you-have-to-try)
- [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix)