AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, test, deploy, and manage AI agents for clients using a blend of low-code and pro-code methodologies.

• Create customer-facing AI solutions throughout the entire Application Lifecycle Management (ALM) process, encompassing design, development, testing, deployment, and continuous improvement.

• Construct and integrate multi-model AI agents, carefully selecting and coordinating models based on specific use cases, performance metrics, and cost factors.

• Design and execute Retrieval-Augmented Generation (RAG) solutions, which include document ingestion, vector databases, indexing strategies, and retrieval logic.

• Set up and integrate MCP servers and associated AI infrastructure components necessary for secure and scalable agent operation.

• Implement secure authentication and authorization frameworks for AI agents, covering identity management, permissions, and service-to-service communication.

• Collaborate with clients to grasp their business needs and convert them into scalable AI agent designs.

• Employ sound engineering methodologies such as version control, environment management, testing strategies, and deployment automation.

• Diagnose and enhance AI agents for optimal performance, reliability, and precision.

• Collaborate closely with security, data, and adoption teams to ensure AI solutions are secure, compliant, and meet governance standards.

• Translate engineering efforts into customer empowerment by designing and delivering technical training, workshops, labs, and demonstrations that facilitate the adoption of the AI solutions you create.

• Conduct enablement sessions both virtually and in-person, tailoring the content and depth for executive, technical, and frontline audiences.

• Document architectures, designs, and operational factors as part of customer deliverables and enablement resources.

⛳️ Requirements

• Over 5 years of experience in software engineering, application development, or engineering roles focused on AI/automation.

• Practical experience in creating AI agents or AI-driven applications using both low-code and pro-code frameworks.

• Profound knowledge of AI concepts and architectures, including model inference, orchestration, and agent design patterns.

• Hands-on experience with MCP servers, agent runtimes, or comparable AI execution frameworks.

• Strong background in designing and implementing RAG architectures, including vector databases and retrieval pipelines.

• Experience with multi-model AI strategies, including the selection, integration, and management of multiple models within a single solution.

• Solid understanding of authentication, identity, and security measures in application and API development.

• Familiarity with ALM best practices such as source control, CI/CD, environment promotion, and testing.

• Capacity to engage directly with customers during solution design and delivery initiatives.

• Excellent verbal communication and public speaking skills, with the confidence to lead live workshops, demonstrations, and training sessions.

• Ability to simplify complex or technical concepts into clear, practical learning experiences for non-technical audiences.

• Willingness to travel for work and deliver on-site engagements as part of customer projects.

• Strong problem-solving abilities and adaptability in rapidly changing technical environments.

🏝️ Benefits

• N/A