Overview
Remote
On Site
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
Skills
API
Agile
Amazon SageMaker
Amazon Web Services
Artificial Intelligence
Cloud Computing
Kubernetes
Language Models
JavaScript
Large Language Models (LLMs)
Docker
Data Modeling
Generative Artificial Intelligence (AI)
Machine Learning Operations (ML Ops)
Node.js
Orchestration
Performance Tuning
Problem Solving
Continuous Delivery
Microservices
Machine Learning (ML)
Microsoft Azure
Backend Development
Job Details
Job Title: Senior GenAI Developer
Location: Dallas, TX or Remote (2nd Priority)
Job Summary:
We are looking for an experienced Senior GenAI Developer with deep expertise in Prompt Engineering, RAG (Retrieval-Augmented Generation) architecture, and building AI-driven applications. The ideal candidate will have strong backend development skills, particularly in Node.js, JavaScript, or TypeScript, and hands-on experience with language models (LLMs) and AI system deployment.
Key Responsibilities:
- Design and implement RAG architectures to build scalable AI applications that leverage external knowledge for improved response quality.
- Develop, optimize, and experiment with AI prompts and prompt engineering techniques to enhance model accuracy and usability.
- Fine-tune and integrate large language models (LLMs) into backend applications for customized AI functionality.
- Build and maintain scalable, robust backend systems supporting AI features, using modern backend technologies.
- Develop APIs and microservices for seamless integration of AI models and pipelines.
- Optimize GenAI pipelines focusing on system performance, latency, and cost-efficiency.
Required Skills & Qualifications:
- Proven expertise in Prompt Engineering and AI prompt optimization strategies.
- Strong understanding of RAG architecture and experience with LLM fine-tuning.
- Proficiency in backend development using Node.js, JavaScript, or TypeScript.
- Hands-on experience with AI model deployment, cloud AI services (e.g., AWS Sagemaker, Azure AI, Google AI), and API development.
- Knowledge of Data Modeling, SQL, and building data pipelines to support AI workflows.
- Familiarity with Vector Databases (e.g., Pinecone, Weaviate), Embeddings, and AI-driven search technologies.
- Experience with MLOps, including CI/CD pipelines for AI models and performance tuning.
- Strong problem-solving skills and ability to work in an agile development environment.
Preferred:
- Experience working in a startup or fast-paced AI/ML environment.
- Knowledge of cloud platforms (AWS, Azure, Google Cloud Platform) and container orchestration (Kubernetes, Docker).
- Exposure to other AI/ML frameworks and tools such as TensorFlow, PyTorch, or Hugging Face.
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.