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AI Engineer

AI Engineer

Resource Informatics GroupMalvern, PA, United States
3 days ago
Job type
  • Full-time
Job description

AI Engineer

Location : Malvern, PA (3 days onsite) - need to be onsite day one

Duration : 6-12 months

Role : GenAI Application Engineer (Mid-Level, AWS Focus)

About the Role

We're building a new GenAI engineering team focused on delivering intelligent, scalable solutions using Amazon Bedrock and Amazon Q Business. This mid-level role is ideal for hands-on developers passionate about AI agent orchestration, prompt engineering, and cloud-native architecture. You'll help shape the future of internal platforms by designing multi-step workflows, building reusable agent libraries, and driving responsible AI adoption across the enterprise.

Responsibilities

  • Design, develop, and deploy GenAI applications using Amazon Bedrock and Amazon Q Business
  • Build and orchestrate AI agents to support multi-step workflows across internal platforms
  • Develop reusable prompt libraries and agent strategies for enterprise use cases
  • Ensure GenAI implementations align with responsible AI standards and governance
  • Automate code generation, debugging, and consistency using LLMs and agentic frameworks
  • Present GenAI capabilities and demos at internal forums and engineering communities
  • Share best practices, prompt strategies, and use cases within the GenAI Community of Practice
  • Participate in discovery events to identify and scope new GenAI opportunities

Minimum Qualifications

  • 3-5 years of hands-on development experience in cloud environments (AWS preferred)
  • Strong proficiency in Python, JavaScript, or Java
  • Experience with AWS services including Lambda, S3, CloudFormation, ECS, and EventBridge
  • Proven experience building GenAI or agentic applications in AWS
  • Solid understanding of LLMs, RAG architecture, and prompt engineering techniques
  • Preferred Qualifications

  • Familiarity with Amazon Q Business and Bedrock integration patterns
  • Experience with observability tools (e.g., CloudWatch, Splunk)
  • Exposure to AI governance and responsible AI frameworks
  • Contributions to internal AI communities or open-source GenAI projects.
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