> Markdown version of [/jobs/ext/2120229-backend-ai-engineer](https://www.wearedevelopers.com/jobs/ext/2120229-backend-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). --- # Backend AI Engineer - **Company:** Genesis10 - **Location:** San Diego, CA, United States (Remote available) - **Experience:** Experienced - **Salary:** $89,440.0 - $110,240.0 - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Design Documents, Design of User Interfaces, Python (Programming Language), PostgreSQL, Machine Learning, Object-Oriented Software Development, Performance Tuning, Software Tools, Next.js, SQL Databases, WebSocket, Google Cloud, Pytorch, ReactJS, Flask (Web Framework), Large Language Models, Prompt Engineering, Generative AI, Backend, Git, Fastapi, Containerization, Kubernetes, Front End Software Development, Restful APIs, Streamlit Framework, Docker, Microservices - **Published:** August 19, 2026 - **Apply:** https://www.dice.com/job-detail/ae74e0de-6229-43cc-b5e9-6f1af1d213e2 ## About the Role * Bachelor's degree in Software/Computer/IT/Systems/Biomedical Engineering or a related technical discipline * 4+ years of professional software/ML engineering experience, with a dedicated AI/ML focus in the last 1-2 years * Hands-on experience with the Gemini model family and Vertex AI, including deployment, grounding, and integration * Experience with containerization (Docker) and deploying services via Cloud Run or GKE (Kubernetes) * Proficiency in Python and modern ML/AI frameworks (PyTorch, LangChain, LangSmith) * Proven experience building AI/LLM agents and tool-calling systems in Python against unstructured, multi-source data * Expertise in RAG pipelines, prompt engineering, context tuning, grounding, and Vector Databases (e.g., Milvus, Postgres/Pgvector) * Demonstrated ability to ingest, clean, extract, and structure text, tables, and images from unstructured documents (PDFs, design docs, etc) * Software Skills: Python (AsyncIO, OOP), SQL, PyTorch, LangChain, LangSmith, Vertex AI SDK, FastAPI, Flask, REST APIs, SSE, Milvus, Pgvector, Docker, Google Cloud Platform (Vertex AI, Cloud Run, GKE), Git Desired Skills: * Direct experience designing and deploying high-throughput REST APIs (e.g., FastAPI/Flask) * Familiarity with medical device development regulations and compliance (e.g., FDA guidelines, ISO 13485) * Experience integrating multiple LLM APIs beyond a single vendor (e.g., OpenAI, AWS Bedrock, Anthropic Claude) * Front-end development/integration experience for UI design (e.g., Streamlit, Gradio, React/Next.js integration) * Professional certifications specific to AI/ML (e.g., Certified AI Professional / CAIP, Google Cloud ML Engineer) ## Description This role focuses on developing and implementing generative AI solutions, including building robust RAG pipelines, fine-tuning LLMs, and creating high-performance APIs. The ideal candidate will have extensive experience with Google Gemini/Vertex AI, Python, and modern AI frameworks to handle unstructured, multi-source data within a regulated domain., * Craft and refine effective prompts for RAG, grounding, and context tuning to achieve optimal AI performance * Develop asynchronous microservices (FastAPI) using Server-Sent Events (SSE) or WebSockets to stream real-time LLM responses * Design, develop, and implement robust Vector Databases using LLMs and modern retrieval technologies * Build and optimize pipelines to extract and structure multi-modal data (tables, text, images) from unstructured documents * Fine-tune and train generative AI models using engineering data and domain knowledge * Design and implement scalable backend APIs (FastAPI/REST) and UI integration interfaces * Develop backend functionalities to automatically generate technical requirements from design documents and user stories * Thoroughly document architecture, code, REST endpoints, and model training procedures * Partner closely with Subject Matter Experts (SMEs), System Engineers, and V&V Test teams to optimize AI-powered workflows * Implement hallucination checks, PII masking, and guardrails for medical device context, and track token usage, latency, and costs ## Related Videos - [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) - [Intro to FastAPI](https://www.wearedevelopers.com/videos/462-intro-to-fastapi) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Building and Deploying Multi-Agent Systems with ADK and Vertex AI](https://www.wearedevelopers.com/videos/1918-building-and-deploying-multi-agent-systems-with-adk-and-vertex-ai) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)