Ai Engineer Jobs

About The Position

Requirements

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related technical field.
• At least 5 years of software engineering experience.
• At least 3 years of experience developing and supporting production-grade full stack or backend applications using C#, ASP.NET, Angular, REST APIs, and relational or NoSQL databases.
• At least 2 years of experience working with cloud-native technologies, CI/CD pipelines, containerization, and Kubernetes-based deployment environments.
• At least 1 year of hands-on experience designing and implementing AI-enabled solutions, including custom AI agents, prompt engineering, RAG systems, or LLM integrations.
• Demonstrated experience designing scalable software architectures and owning applications through design, implementation, deployment, and ongoing operational support.

Nice To Haves

• At least 2 years of experience applying AI-assisted development practices to improve software engineering productivity and reduce development cycles.
• Experience designing and implementing custom AI agents using MCP or similar structured agent and tool orchestration frameworks.
• Demonstrated success deploying AI-enabled applications in mission-critical or high-availability environments with stringent reliability requirements.
• Experience evaluating, refining, and operationalizing AI-generated code and outputs for production use.
• Experience building interoperable AI ecosystems that integrate multiple models, tools, APIs, and data sources without tightly coupled architectures.

Responsibilities

• Design, develop, test, deploy, and support full stack applications, owning features throughout the entire software development lifecycle.
• Build and implement personalized AI assistants to automate workflows, support decision-making, provide summarization, and implement multi-step business processes.
• Develop integrations using Model Context Protocol (MCP) or similar frameworks to enable interoperability between AI models, tools, and systems.
• Integrate applications with AI services such as LLMs, embeddings, search platforms, and RAG solutions while ensuring security, reliability, scalability, and performance.
• Apply AI-assisted development tools to accelerate coding, testing, documentation, and refactoring while maintaining engineering standards and code quality.

Benefits

• Medical insurance plans
• Dental insurance plans
• Vision insurance plans
• Income-protection benefit programs for illness or injury
• Paid family leave
• Paid time off
• Paid holidays