AI Engineer II
Role summary
The AI Engineer II will design, build, and deliver production-grade generative AI applications, focusing on application engineering and system design rather than traditional data science. This hands-on, ownership-driven role translates business needs into scalable GenAI solutions, including full-stack development, LLM integrations (RAG, prompt engineering), and API workflows. The position requires strong Python proficiency, experience with cloud platforms (AWS, Azure, GCP), DevOps practices (CI/CD), and API design. The role emphasizes balancing rapid prototyping with enterprise-grade reliability, security, and governance, operating with a high degree of independence in complex enterprise environments. Familiarity with agentic frameworks and experience in the energy sector are preferred.
AI Engineer II (Generative AI)
Location:
Juno Beach, FL (preferred, can offer remote for the right candidate)
Duration:
12-Month Contract
Pay Rate:
$37-42/hour
Overview
The AI Engineer II will design, build, and deliver production-grade generative AI applications that solve real business problems across innovation and pilot initiatives.
This is a highly hands-on, ownership-driven role with responsibility spanning concept, architecture, implementation, and production deployment.
You will operate with a high degree of independence, acting as an end-to-end engineer who translates business needs into scalable GenAI solutions. The role focuses on application engineering, system design, and enterprise readiness rather than traditional data science or model training.
Technologies of interest include (but are not limited to): large language models (LLMs), automation, cloud platforms, agentic workflows, and industrial domains such as energy systems.
Key Responsibilities
- Design and deliver generative AI applications from concept through production
- Translate business requirements into scalable GenAI system architectures
- Build and maintain full-stack applications, including APIs and LLM-powered tools
- Implement LLM integrations using approaches such as RAG, prompt engineering, tool calling, and API workflows
- Balance rapid prototyping with enterprise-grade reliability, security, and governance
- Apply DevOps best practices (CI/CD, monitoring, scalable deployments)
- Collaborate with cross-functional teams while owning technical delivery independently
- Evaluate and prototype emerging GenAI tools and platforms
- Communicate technical concepts and trade-offs to non-technical stakeholders
- Stay current with industry trends and evolving GenAI capabilities
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, IT, or related field
- 3-5+ years of experience in software engineering, AI engineering, or similar roles
- Strong proficiency in Python
- Experience building and deploying production software systems
- Full-stack development experience (frontend and backend)
- Experience with cloud platforms (AWS, Azure, or GCP)
- Knowledge of modern cloud architectures
- DevOps experience (CI/CD pipelines, containerization, deployment automation)
- Experience designing and consuming APIs
- Familiarity with version control tools (e.g., Git)
- Strong problem-solving and communication skills
- Ability to work independently in complex enterprise environments
Preferred Qualifications
- Experience building LLM-powered applications
- Familiarity with agentic/orchestration frameworks (e.g., LangChain, LangGraph, AutoGen)
- Experience in energy, utilities, or industrial sectors
...
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