AI Engineer

Precision Inc.
Dallas, TX, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Software Applications Microsoft Azure Cloud Computing Computer Programming Information Retrieval Python (Programming Language) Machine Learning Performance Tuning OpenAI Cloud Services
+33 more
Tensorflow Software Deployment SQL Databases LangChain ReactJS Retrieval-Augmented Generation Transfer Learning Flask (Web Framework) Large Language Models Prompt Engineering Llamaindex Generative AI Backend Agentic-AI Fastapi Containerization AI Platforms AngularJS Kubernetes Information Technology HuggingFace CrewAI Cosmos DB Machine Learning Operations Front End Software Development Claude Virtual Agents Google Gemini Streamlit Framework Natural Language Understanding Docker Natural Language Generation Agent2Agent Protocol

Job description

You will work across front-end, back-end, and AI services, leveraging frameworks such as React.js, FastAPI, and Azure AI Foundry, while exploring the latest Generative AI, RAG, and agentic frameworks., AI Development

  • Design, prototype, and productionize AI agents capable of intelligent communication, information retrieval, and task execution.
  • Develop and optimize high-performance code for LLM-based and Agentic AI models.
  • Drive the roadmap for Generative AI use cases, ensuring scalability and real-world impact.

Collaboration with Teams

  • Partner with transformation, engineering, and business teams to tailor AI agents for domain-specific workflows.
  • Work with AI platform teams to ensure robust infrastructure, observability, and monitoring.

Integration & Deployment

  • Lead and contribute to AI projects from POC to production.
  • Deploy, monitor, and scale AI solutions on Azure, AWS, or GCP, using containerized environments (Docker, Kubernetes).
  • Integrate AI pipelines into front-end and back-end applications.

Continuous Learning & Optimization

  • Stay current with cutting-edge AI research (Generative AI, RAG, agentic frameworks).
  • Perform testing, validation, and performance tuning for compliance and reliability.
  • Research and publish internal training resources, workshops, and documentation to upskill teams.

Technologies & Tools

  • LLMs: OpenAI, LLaMA, Mistral, Gemini, Claude, Grok
  • Agentic Frameworks: Langchain, CrewAI, A2A, LLaMAIndex, RAG pipelines
  • Programming & Frameworks: Python, FastAPI, SQL, CosmosDB, Flask, Streamlit, Chainlit
  • Frontend: React, Angular
  • Cloud & Deployment: Azure Faundry, Azure OpenAI, Docker, Kubernetes, VectorDBs
  • Other Tools: Hugging Face Transformers, TensorFlow, Cognitive Services

Requirements

We are seeking an AI Engineer with proven experience in building and scaling AI-powered applications. This role combines hands-on development with AI research and training responsibilities. The ideal candidate will design, prototype, and productionize AI agents, integrate them into enterprise workflows, and publish training resources to help teams adopt and apply AI effectively., * Bachelor’s degree in computer science, Data Science, AI/ML, or related field (required).

  • Master’s degree (preferred).

Experience

  • 7-8 years of hands-on experience in developing, deploying, and scaling AI/ML solutions.
  • Proven success with Generative AI, NLP/NLU, and AI agent frameworks.
  • Experience leading AI-focused projects and collaborating with business & technical stakeholders.

Technical Skills

  • Strong proficiency in Python and SQL.
  • Familiarity with front-end technologies (React, Angular).
  • Experience with containerization and cloud services (Azure/AWS/GCP).
  • Solid understanding of prompt engineering, LLM fine-tuning, and RAG techniques.

Soft Skills

  • Clear communication - able to explain complex AI concepts to technical and non-technical audiences.
  • Collaboration & teamwork - works well across engineering, business, and research teams.
  • Adaptability - thrives in fast-moving environments with evolving AI tools.
  • Curiosity & learning mindset - passionate about exploring and teaching new AI capabilities.
  • Problem-solving & critical thinking - proactive in diagnosing issues and designing innovative solutions.
  • Knowledge sharing - ability to research and publish training materials to foster AI adoption across the organization.

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