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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Python/GenAI Developer - **Company:** CAI, Inc. - **Location:** Dover, DE, United States (Remote available) - **Salary:** $135,200.0 - $145,600.0 - **Contract:** Permanent contract - **Skills:** AI Evaluation, Microsoft Excel, Application Programming Interfaces (APIs), Artificial Intelligence, User Authentication, BigQuery, Cloud Computing, Cloud Storage, Continuous Integration, Software Debugging, File Systems, Github, Graph Database, Identity and Access Management, Information Retrieval, JSON, Python (Programming Language), Metadata, OAuth, Object-Oriented Software Development, Package Management Systems, Azure Machine Learning, Software Engineering, Unstructured Data, Web Application Frameworks, Data Logging, Data Processing, Google Cloud, Enterprise Software Applications, ReactJS, Retrieval-Augmented Generation, Flask (Web Framework), Delivery Pipeline, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Backend, Agentic-AI, Vertex AI Vector Search, Gitlab, Git, Fastapi, Event Driven Architecture, Containerization, Integration Tests, Production Code, Front End Software Development, Api Design, Graph RAG, Restful APIs, Prompt Orchestration, Software Version Control, Api Management, Serverless Computing, Docker - **Published:** October 17, 2026 - **Apply:** https://dejobs.org/x/x/A6F7E158342E49A4AA319AD085E333FF/job/ ## About the Role * Minimum 4-7 years of software development experience, with strong hands-on experience in Python backend development; programming fundamentals, object-oriented design, modular coding, exception handling, testing, and package management * Minimum 1-2 years of practical experience with Generative AI and LLM-based applications including prompt engineering, structured outputs, model invocation, response validation, token usage, and basic evaluation concepts * Minimum 1-2 years of practical experience RAG solutions including document ingestion, chunking, embeddings, vector retrieval, metadata filtering, reranking, and grounding * Experience building REST APIs using FastAPI, Flask, or similar Python frameworks; endpoint development, request/response models, authentication, async processing, status handling, and API integration * Hands-on experience working with Google Cloud Platform, especially Cloud Run, Cloud Storage, Vertex AI, BigQuery, Pub/Sub, IAM, and Secret Manager * Experience integrating AI/ML services into enterprise applications using APIs, authentication, asynchronous processing, and cloud-native services * Experience with cloud-native development including Docker, service accounts, environment variables, secrets, CI/CD, deployment, and runtime troubleshooting * Experience processing structured and unstructured data formats such as JSON, JSONL, Excel, CSV, PDF, Word documents, and text * Experience with source control, CI/CD, containerization, and deployment workflows using Git, Docker, GitLab/GitHub, and cloud deployment pipelines * Exposure to debugging distributed or cloud-hosted applications using logs, monitoring, request tracing, and error analysis * Experience working in Agile delivery teams and collaborating with cross-functional stakeholders Preferred: * Experience with Agentic AI frameworks or multi-step AI orchestration * Familiarity with Vertex AI Vector Search, Graph RAG, or knowledge graph concepts * Experience with Pub/Sub-based asynchronous processing and event-driven architectures * Understanding of OAuth, service-to-service authentication, IAM, signed URLs, and secure API integration * Exposure to React or frontend integration is useful but not mandatory * Familiarity with AI evaluation metrics such as groundedness, relevance, completeness, coherence, and confidence scoring * Healthcare-domain exposure is beneficial, especially where the solution involves enterprise workflow, requirements, or document intelligence Physical Demands * Ability to safely and successfully perform the essential job functions consistent with the ADA and other federal, state and local standards * Sedentary work that involves sitting or remaining stationary most of the time with occasional need to move around the office to attend meetings * Ability to conduct repetitive tasks on a computer, utilizing a mouse, keyboard, and monitor ## Description As a Python/GenAI Developer, you will Build and enhance enterprise AI applications through Python development, Generative AI integration, API design, data processing, and cloud-based deployment., CAI is seeking a Python/GenAI Developer to build and support Python-based backend services and AI solutions leveraging LLMs, RAG, FastAPI, and Google Cloud technologies. The role focuses on delivering secure, scalable, and reliable AI-enabled applications while collaborating with business and technical stakeholders throughout the software development lifecycle. This position is contract and remote., * Design, develop, and maintain Python-based backend services and APIs for AI-enabled applications, with strong emphasis on clean, modular, production-ready code * Build and integrate Generative AI workflows using LLMs, RAG pipelines, prompt orchestration, and structured-output processing * Develop FastAPI-based REST endpoints to support file processing, pipeline execution, asynchronous workflows, and integration with external enterprise applications * Implement retrieval workflows using GCP services such as Vertex AI, Vertex AI Search, Cloud Storage, BigQuery, Pub/Sub, Secret Manager, and Cloud Run * Develop data-processing logic for structured and unstructured inputs, including document parsing, metadata generation, validation, transformation, and downstream persistence * Support integration testing, debugging, deployment, logging, monitoring, and troubleshooting of AI applications across development and QA environments * Collaborate with solution architects, cloud infrastructure teams, product owners, and business stakeholders to translate requirements into working AI features and scalable backend components * Contribute to prompt engineering, output validation, error handling, retry logic, and guardrails to improve reliability of AI pipeline responses * Maintain technical documentation, API contracts, configuration files, deployment artifacts, and reusable engineering components