Abode Techzone LLC
Overview
Job Title:
Lead Developer - GenAI & RAG Systems Location:
Austin, TX Hybrid with 3 days onsite Type:
Contract Only local candidates Job Summary We are seeking a highly skilled Lead Developer with strong expertise in Python, Generative AI (LLMs, RAG pipelines, Embeddings), and GCP Cloud Services. The ideal candidate will have hands-on experience in building production-grade AI / ML systems with UI integration, managing secure enterprise deployments, and ensuring scalability and compliance. Key Responsibilities Responsibilities
Design, build, and deploy Retrieval-Augmented Generation (RAG) pipelines for enterprise GenAI solutions Develop scalable LLM-based applications using embeddings, vector databases, and prompt engineering best practices Work with Azure Functions, Azure OpenAI, Azure ML, Cosmos DB, and Blob Storage for cloud-native implementations Build robust Python microservices for real-time AI inference and data processing Integrate secure authentication mechanisms (SSO, OAuth, JWT) ensuring security and compliance standards Collaborate with front-end engineers to build interactive UIs for AI workflows Lead and mentor junior developers in AI / ML engineering best practices Ensure performance, fault tolerance, and observability in deployed applications Required Skills & Experience
8+ years of experience in software engineering, with at least 3+ years in AI / ML systems Expertise in Python and hands-on experience with RAG pipelines, LLMs (GPT, Claude, LLaMA, etc.), and embedding models GCP stack: Vertex AI, Cloud Functions, Firestore, BigQuery Deep understanding of enterprise integrations including SSO, authentication, data privacy, and compliance Experience with vector databases like Pinecone, FAISS, Weaviate, or Azure Cognitive Search Familiarity with front-end / UI development frameworks (e.g. React, Streamlit, Flask for dashboards) Proven record of deploying production-grade AI applications with UI and backend integration Preferred Skills
Experience with LangChain, LlamaIndex, or similar GenAI orchestration frameworks Knowledge of MLOps practices and tools (e.g., MLflow, Azure DevOps) Familiarity with CI / CD pipelines and containerization using Docker & Kubernetes
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Job Title:
Lead Developer - GenAI & RAG Systems Location:
Austin, TX Hybrid with 3 days onsite Type:
Contract Only local candidates Job Summary We are seeking a highly skilled Lead Developer with strong expertise in Python, Generative AI (LLMs, RAG pipelines, Embeddings), and GCP Cloud Services. The ideal candidate will have hands-on experience in building production-grade AI / ML systems with UI integration, managing secure enterprise deployments, and ensuring scalability and compliance. Key Responsibilities Responsibilities
Design, build, and deploy Retrieval-Augmented Generation (RAG) pipelines for enterprise GenAI solutions Develop scalable LLM-based applications using embeddings, vector databases, and prompt engineering best practices Work with Azure Functions, Azure OpenAI, Azure ML, Cosmos DB, and Blob Storage for cloud-native implementations Build robust Python microservices for real-time AI inference and data processing Integrate secure authentication mechanisms (SSO, OAuth, JWT) ensuring security and compliance standards Collaborate with front-end engineers to build interactive UIs for AI workflows Lead and mentor junior developers in AI / ML engineering best practices Ensure performance, fault tolerance, and observability in deployed applications Required Skills & Experience
8+ years of experience in software engineering, with at least 3+ years in AI / ML systems Expertise in Python and hands-on experience with RAG pipelines, LLMs (GPT, Claude, LLaMA, etc.), and embedding models GCP stack: Vertex AI, Cloud Functions, Firestore, BigQuery Deep understanding of enterprise integrations including SSO, authentication, data privacy, and compliance Experience with vector databases like Pinecone, FAISS, Weaviate, or Azure Cognitive Search Familiarity with front-end / UI development frameworks (e.g. React, Streamlit, Flask for dashboards) Proven record of deploying production-grade AI applications with UI and backend integration Preferred Skills
Experience with LangChain, LlamaIndex, or similar GenAI orchestration frameworks Knowledge of MLOps practices and tools (e.g., MLflow, Azure DevOps) Familiarity with CI / CD pipelines and containerization using Docker & Kubernetes
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