Applied AI Engineer - Telecommuncations

Ready to take the next step in your career?

Join a leading provider of fiber-based broadband services, delivering multi-gigabit connectivity, Ethernet, dark fibre, and fiber optic and wireless infrastructure solutions across the United States. The organization is focused on expanding a large-scale open-access fibre network to provide fast, reliable, high-capacity connectivity nationwide.

This company is looking for an Applied AI Engineer to build and operate shared AI platforms, reusable AI services, and cross-functional AI capabilities across the business. The role focuses on RAG, AI agents, orchestration frameworks, retrieval infrastructure, and internal tooling, working closely with Data Engineering and Embedded AI teams to develop scalable, secure, and cost-effective AI solutions.

If you would like to learn more about this opportunity, feel free to reach out and apply today!

Responsibilities:

• Build and operate shared AI platform, including internal AI gateways, retrieval infrastructure, and reusable AI services. 
• Design, develop, deploy, and support end-to-end LLM applications utilizing orchestration frameworks, agents, prompt engineering, retrieval systems, and evaluation methodologies. 
• Build and maintain scalable RAG solutions leveraging structured, unstructured, and geospatial data sources. 
• Develop reusable components, APIs, frameworks, and tooling that accelerate AI adoption across multiple teams and business functions. 
• Deploy and operate AI workloads within Azure cloud environments utilizing containerized architectures and modern deployment practices. 
• Partner with Embedded AI Engineers on complex, cross-functional initiatives that span multiple business domains. 
• Monitor solution quality, adoption, cost efficiency, reliability, and business impact, continuously refining capabilities as needed. 
• Implement best practices for AI governance, observability, evaluation, and operational excellence. 
• Optimize AI systems for cost, performance, scalability, and maintainability. 
• Utilize AI-powered tools to improve personal productivity and accelerate software development and innovation. 

Skills/Must Have:

• Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related discipline, or equivalent practical experience. 
• 3 to 5 years of software engineering experience, including recent hands-on experience building LLM-based applications. 
• Strong proficiency in Python. 
• Demonstrated experience building and maintaining RAG systems, including embeddings, vector databases, retrieval architectures, and evaluation frameworks. 
• Experience designing and deploying AI agents, orchestration frameworks, and production-grade AI applications. 
• Experience deploying and operating services in cloud environments, preferably Microsoft Azure. 
• Experience working with containerized platforms and modern application deployment approaches. 
• Strong understanding of performance, scalability, reliability, and cost considerations associated with token-based AI systems. 
• Working knowledge of SQL and experience utilizing structured and geospatial datasets. 
• Strong analytical, problem-solving, and communication skills. 

Desirable Skills:

• Experience with AI gateways, chat interfaces, and reusable AI platform architectures. 
• Experience implementing evaluation frameworks, guardrails, governance controls, and AI safety capabilities. 
• Experience working with geospatial data and location-based analytics. 
• Experience with MLOps practices including deployment automation, monitoring, CI/CD, and operational support for AI systems. 
• Experience supporting enterprise AI initiatives in data-intensive environments.
• AI Platform Engineering: Designs and maintains scalable, reusable AI capabilities that support enterprise-wide adoption. 
• LLM Application Development: Builds robust production-grade solutions leveraging modern AI architectures and frameworks. 
• Technical Leadership: Influences architecture, standards, and engineering best practices across teams. 
• Cross-Functional Collaboration: Partners effectively with engineering, data, and business teams to deliver impactful solutions. 
• Operational Excellence: Prioritizes reliability, observability, security, performance, and maintainability. 
• Innovation & Automation: Continuously identifies opportunities to improve business outcomes through AI-enabled capabilities. 
• Data-Driven Decision Making: Uses metrics, evaluation, and adoption data to guide continuous improvement. 

Salary:

• $150k - $165k