Senior Generative AI Engineer

Hybrid in Austin, TX, US • Posted 18 hours ago • Updated 18 hours ago
Contract W2
12 Months
No Travel Required
Able to Sponsor
On-site
$55 - $65/hr
Fitment

Dice Job Match Score™

🛠️ Calibrating flux capacitors...

Job Details

Skills

  • Docker
  • Artificial Intelligence
  • Autogen
  • Cloud Computing
  • Collaboration
  • Generative Artificial Intelligence (AI)
  • Communication
  • Computer Science
  • Data Science
  • Machine Learning Operations (ML Ops)
  • Microservices
  • Open Source
  • Performance Tuning
  • Stakeholder Management
  • Testing
  • Vector Databases
  • Workflow
  • Prompt Engineering
  • Semantic Search
  • Software Engineering
  • Debugging
  • DevOps
  • Kubernetes
  • Large Language Models (LLMs)
  • Python

Summary

Job Summary

We are seeking an experienced Generative AI Engineer to design, develop, and deploy enterprise-grade AI applications powered by Large Language Models (LLMs). The ideal candidate will have a strong software engineering background combined with hands-on expertise in Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, model fine-tuning, vector databases, and cloud-based AI platforms.

You will collaborate with business stakeholders, data scientists, and engineering teams to build scalable, secure, and production-ready AI solutions that solve real-world business challenges.


Key Responsibilities

  • Design, build, and deploy enterprise Generative AI applications.
  • Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases.
  • Build AI Agents and multi-agent workflows using frameworks such as LangGraph, CrewAI, or AutoGen.
  • Develop applications using Large Language Models (OpenAI GPT, Claude, Gemini, Llama, Mistral, etc.).
  • Create prompt engineering strategies for improved model accuracy and performance.
  • Fine-tune open-source LLMs using LoRA, PEFT, Hugging Face Transformers, and related techniques.
  • Integrate AI models with enterprise applications using REST APIs and microservices.
  • Build scalable backend services in Python.
  • Develop semantic search solutions using embeddings and vector databases.
  • Deploy AI applications using Docker, Kubernetes, and cloud platforms.
  • Optimize model performance, latency, and inference costs.
  • Implement AI governance, monitoring, and responsible AI practices.
  • Collaborate with DevOps and MLOps teams for production deployment.
  • Perform testing, debugging, and performance tuning of AI applications.
  • Stay current with emerging AI technologies and best practices.

Required Qualifications

  • Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • 10–15+ years of software engineering experience.
  • 3+ years of hands-on Generative AI/LLM development experience.
  • Strong experience building enterprise AI applications.
  • Excellent communication and stakeholder management skills.
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.
  • Dice Id: 91138713
  • Position Id: 9017376
  • Posted 18 hours ago
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