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Compunnel, Inc.
AI Architect
Career Insights for Generative Artificial Intelligence Engineer
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Based on Pennsylvania data
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What they do
A Generative Artificial Intelligence Engineer develops, designs, and manages generative models and algorithms that support the generation of new content in the form of images, text, audio, and other multimedia. They utilize GPTs, GANs, VAEs, and other deep learning architectures to craft systems capable of generating data. May work with data scientists, machine learning engineers, and software developers.
$109,885 / year median in Pennsylvania
Job Description
Job Summary We are seeking an experienced AI Architect to design, build, and deploy enterprise-scale AI and LLM solutions. The role requires a hands-on technical leader with expertise in AI engineering, cloud infrastructure, software development, and advanced agentic workflows using AWS Agent Core. The ideal candidate will architect end-to-end AI/ML platforms, develop production-grade applications, establish scalable AI delivery practices, and mentor engineering teams. Key Responsibilities
- Design and implement end-to-end AI/ML architectures and production-ready solutions using modern AI frameworks and cloud-native technologies.
- Architect, provision, and manage secure, scalable, and resilient AI infrastructure on AWS using Terraform and Infrastructure-as-Code principles.
- Build, optimize, and deploy advanced multi-agent systems and orchestration frameworks using AWS Agent Core, Amazon Bedrock Agents, and Knowledge Bases.
- Develop and maintain data, model, and inference pipelines integrating LLMs, vector databases, and enterprise applications.
- Implement Retrieval-Augmented Generation (RAG) solutions for enterprise AI use cases.
- Develop and optimize prompt engineering strategies to improve AI solution performance and outcomes.
- Establish and drive best practices across AI Engineering, MLOps, and LLMOps.
- Ensure AI deployments are scalable, reliable, secure, and governed.
- Provide technical leadership and mentorship to engineering teams.
- Collaborate with business and technology stakeholders to define and deliver AI initiatives.
- Lead AI solutions from proof of concept through production implementation. Required Qualifications
- Strong experience designing and deploying AI/ML and Generative AI solutions from proof of concept through production implementation.
- Strong experience with AI engineering, cloud infrastructure, and software development.
- Hands-on experience architecting and implementing enterprise-scale AI and LLM solutions.
- Strong experience with AWS cloud technologies and cloud-native AI architectures.
- Experience with Terraform and Infrastructure-as-Code principles.
- Experience building multi-agent AI systems and orchestration frameworks.
- Experience with AWS Agent Core, Amazon Bedrock Agents, and Knowledge Bases.
- Experience developing data, model, and inference pipelines.
- Experience integrating LLMs, vector databases, and enterprise applications.
- Strong experience implementing Retrieval-Augmented Generation (RAG) solutions.
- Experience with prompt engineering and optimization strategies.
- Strong understanding of AI Engineering, MLOps, and LLMOps practices.
- Demonstrated technical leadership, mentoring, and stakeholder collaboration skills.