Lead Developer GenAI & RAG Systems

Overview

Hybrid
Depends on Experience
Contract - Independent
Contract - W2
Contract - 12 Month(s)
No Travel Required

Skills

Artificial Intelligence
Authentication
Cloud Computing
Continuous Delivery
Continuous Integration
Cosmos-Db
Dashboard
DevOps
Docker
Flask
Generative Artificial Intelligence (AI)
Good Clinical Practice
Google Cloud Platform
Kubernetes
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Management
Mentorship
Microservices
Microsoft Azure
OAuth
Orchestration
Privacy
Prompt Engineering
Python
React.js
Real-time
Regulatory Compliance
SSO
Scalability
Software Engineering
Storage
UI
Vector Databases
Vertex

Job Details

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 Google Cloud Platform 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

  • 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
  • Google Cloud Platform 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
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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