> Markdown version of [/jobs/ext/2116892-senior-ai-llm-engineer-python-remote](https://www.wearedevelopers.com/jobs/ext/2116892-senior-ai-llm-engineer-python-remote). 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). --- # Senior AI/LLM Engineer (Python) - Remote - **Company:** KAKE,INC - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Infrastructure, Data Stores, Distributed Systems, Python (Programming Language), PostgreSQL, Machine Learning, Open Source Technology, Redis, Tensorflow, Software Deployment, Software Engineering, Data Streaming, Enterprise Software Applications, Pytorch, Large Language Models, Prompt Engineering, Backend, Fastapi, Containerization, Scikit Learn, Integration Tests, Apache Kafka, Docker - **Published:** August 19, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pd9zpv2dd8 ## About the Role * Strong proficiency in Python and experience with FastAPI or similar backend frameworks. * Experience working with LLM APIs (e.g., OpenAI, Anthropic, or similar) and frameworks such as LangChain or LlamaIndex. * Experience with RAG architectures, embeddings, and vector databases (e.g., Pinecone, Weaviate, pgvector, or similar). * Hands-on experience with Docker and containerized development environments. * Experience working with PostgreSQL, Redis, or similar data stores. * Strong experience writing functional and integration tests, including evaluation frameworks for AI/LLM output quality. * Excellent written and verbal communication skills in English. * Ability to work independently in a remote, fast-paced environment. Nice-to-Have * Experience fine-tuning or evaluating open-source LLMs. * Familiarity with prompt engineering best practices and agentic workflows. * Experience with distributed systems, streaming (e.g., Kafka), or large-scale applications. * Background in machine learning fundamentals (e.g., scikit-learn, PyTorch, or TensorFlow). * Comfortable working flexible hours to overlap with distributed teams across different time zones. ## Description Senior AI/LLM Engineers with strong Python experience, skilled in designing, building, and productionizing LLM-powered applications and AI systems at scale. It's a great fit for people who enjoy working at the intersection of software engineering and applied AI, and who take ownership from prototyping through production deployment. What you'll build and own * Design, build, and deploy LLM-powered features and applications using Python. * Develop and maintain backend services and APIs (e.g., FastAPI) that expose AI/LLM capabilities to other systems. * Build and optimize RAG pipelines, including embeddings, vector search, and retrieval strategies. * Design, test, and iterate on prompts, agents, and orchestration flows using frameworks such as LangChain, LlamaIndex, or similar. * Integrate with LLM providers and APIs (e.g., OpenAI, Anthropic, open-source models) and manage tradeoffs around cost, latency, and quality. * Evaluate model outputs systematically, building tooling and metrics to test accuracy, safety, and regression across iterations. * Work with containerized environments and data infrastructure (e.g., PostgreSQL, Redis, vector databases) to support reliable AI systems in production. * Collaborate with cross-functional stakeholders to translate ambiguous product needs into technically sound AI solutions. ## Related Videos - [Reducing LLM Calls with Vector Search Patterns - Raphael De Lio (Redis)](https://www.wearedevelopers.com/videos/1714-reducing-llm-calls-with-vector-search-patterns-raphael-de-lio-redis) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [Accelerating Authentication Architecture: Taking Passwordless to the Next Level](https://www.wearedevelopers.com/videos/733-accelerating-authentication-architecture-taking-passwordless-to-the-next-level) - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [13 AI Tools You Have to Try](https://www.wearedevelopers.com/magazine/219-13-ai-tools-you-have-to-try) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this)