Full-Time

AI Engineer

LLMs + C#

Aperia

Aperia

Bolt-on automatic tire inflation system

No salary listed

Frisco, TX, USA + 2 more

More locations: Alpharetta, GA, USA | Omaha, NE, USA

In Person

Bachelor's

Category
AI & Machine Learning (1)
Required Skills
LLM
Claude
Kubernetes
Dynatrace
Pinecone
Microsoft Azure
Agile
React.js
GitHub Actions
NoSQL
Git
Data Structures & Algorithms
Machine Learning
OpenAI
Postgres
Docker
TypeScript
.NET
Microservices
C#
AWS
Jenkins
MongoDB
SCRUM
REST APIs
LangChain
DevOps
Splunk
Angular
Cassandra
Google Cloud Platform
Requirements
  • At least 2 years of software engineering experience with hands-on exposure to Generative AI and/or Large Language Model technologies.
  • Practical experience integrating Large Language Models or AI services into applications.
  • Understanding of prompt engineering, tokens and context windows, embeddings, vector search, Retrieval-Augmented Generation, fine-tuning concepts, function/tool calling, AI agents, and model evaluation.
  • Experience with one or more AI platforms such as Azure OpenAI, OpenAI, Anthropic, AWS Bedrock, or Google Vertex AI.
  • Experience developing AI-powered applications or prototypes using APIs, software development kits, or AI frameworks.
  • Experience using GitHub Copilot, ChatGPT, Claude, or other AI-assisted development tools.
  • Ability to understand, review, debug, and improve AI-generated code.
  • Understanding of responsible AI, including security, privacy, hallucination risks, data protection, and appropriate handling of sensitive information.
  • At least 4 years of professional software development experience.
  • Some hands-on experience with C#/.NET, .NET Core, or .NET 6+.
  • Strong understanding of object-oriented programming, SOLID principles, design patterns, algorithms and data structures, and clean, maintainable code.
  • Experience developing and consuming RESTful APIs.
  • Experience with relational databases such as SQL Server or PostgreSQL.
  • Experience with Git and modern source-control workflows.
  • Understanding of continuous integration and continuous delivery and modern software development practices.
  • Strong debugging, troubleshooting, and problem-solving skills.
  • Experience working in Agile/Scrum environments.
  • Experience with cloud-based applications.
  • Understanding of cloud-native application architecture and microservices.
  • Experience with continuous integration and continuous delivery tools such as Azure DevOps, GitHub Actions, Jenkins, or Harness.
  • Understanding of secure software development and DevSecOps practices.
  • Must be willing to submit to a background investigation and drug test as part of the selection process.
  • Bachelor's degree in Computer Science, Information Systems, or another related field.
Responsibilities
  • Design, develop, and integrate AI/LLM-powered capabilities into enterprise applications.
  • Evaluate and integrate LLM platforms, models, APIs, and AI services such as Azure OpenAI, OpenAI, or similar technologies.
  • Develop solutions using prompt engineering, Retrieval-Augmented Generation, embeddings and semantic search, vector databases, function/tool calling, structured outputs, AI agents and agentic workflows, and context management.
  • Build and consume RESTful APIs to integrate AI capabilities with existing enterprise applications.
  • Develop proof-of-concepts and production-ready AI solutions while evaluating model quality, accuracy, performance, cost, and scalability.
  • Leverage GitHub Copilot and other AI coding assistants to improve software development productivity while maintaining code quality and security.
  • Develop approaches for AI evaluation, testing, monitoring, and validation, including identifying hallucinations and unreliable model responses.
  • Work with business stakeholders to identify practical use cases for AI and translate business requirements into technical solutions.
  • Integrate AI solutions with enterprise data sources, databases, APIs, and existing applications.
  • Participate in architecture and technical design discussions related to AI-enabled applications.
  • Ensure AI solutions follow enterprise security, privacy, compliance, and DevSecOps practices.
  • Research emerging AI/LLM technologies and recommend approaches that can provide business value.
  • Troubleshoot complex technical issues involving applications, APIs, AI services, data, and infrastructure.
  • Mentor team members and share knowledge related to AI/LLM technologies and best practices.
Desired Qualifications
  • Familiarity with Docker and/or Kubernetes.
  • Familiarity with SAST/security tools such as Fortify or similar technologies.
  • Experience with application monitoring and observability tools such as Splunk or Dynatrace.
  • Experience building enterprise AI/LLM applications.
  • Experience implementing Retrieval-Augmented Generation solutions using enterprise documents or databases.
  • Experience with vector databases such as Pinecone, Azure AI Search, Weaviate, Milvus, or pgvector.
  • Experience with AI/LLM frameworks such as LangChain, Semantic Kernel, or LlamaIndex.
  • Experience with AI agents and tool/function calling.
  • Experience developing AI evaluation and testing strategies.
  • Experience integrating LLMs with enterprise APIs and business systems.
  • Familiarity with Azure AI services and Azure OpenAI.
  • Experience with financial services, banking, payments, or other high-volume transactional systems.
  • Experience with APIGEE or API management platforms.
  • Experience with MongoDB, Cassandra, or other NoSQL technologies.
  • Experience with React, Angular, TypeScript, or other modern frontend technologies.

Aperia develops automatic tire inflation technology for commercial fleets. Its Halo Tire Inflator is a bolt-on, self-powered device per wheel that uses wheel rotation to keep tires at optimal pressure without an onboard air connection, with installation taking about 5–10 minutes per wheel. Halo Connect i3 adds smart sensors and two-way communication to monitor tire health, provide predictive analytics, and remotely adjust pressure based on load, temperature, or tire model. The system helps fleets save fuel, extend tire life, and improve safety, and its technology has been adopted by major operators and Ryder as a standard specification.

Company Size

N/A

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

N/A

Simplify Jobs

Simplify's Take

What believers are saying

  • March 2026 Fontaine deal puts Halo Connect inside tractor-trailer coupling visibility.
  • Goodyear’s TaaS agreement and Geotab Marketplace integration expand distribution in 2026.
  • Aperia said Halo passed 100 billion customer miles by January 2026.

What critics are saying

  • PSI, STEMCO, and Hendrickson sell competing ATIS into the same fleets.
  • 2017 NHTSA recall showed adapter-plate fatigue can detach Halo from wheels.
  • Hardware retrofits depend on fleet capex; weak trucking purchasing freezes deployments by 2026.

What makes Aperia unique

  • Halo uses wheel rotation, not onboard air, for automatic inflation.
  • Halo Connect i3 adds two-way telemetry, remote setpoints, and predictive tire analytics.
  • March 2026 Fontaine integration extends Aperia into fifth-wheel safety workflows.

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Benefits

Health Insurance

Health savings account

Dental Insurance

Vision Insurance

401(k) matching

Paid time off

Parental Leave

Disability Insurance

Childcare assistance

Education reimbursement

Fitness Membership

Volunteer Time Off