Applied AI Engineer: Production-Grade AI & Agents

Purpose and Scope

The Applied AI Engineer will help design, develop, and deploy generative and agent-based AI solutions throughout the organization. Work centers on real-world production use cases, focusing on practical AI applications such as agentic workflows, retrieval-augmented generation (RAG), prompt engineering, and AI-driven automation. The role places a strong emphasis on moving projects from experimentation to reliable, well-governed production environments. The AI Engineer is a hands-on, builder-focused role and collaborates closely with software engineers, data engineers, product owners, and business stakeholders to integrate AI capabilities into operational workflows across Tolmar.

Essential Duties & Responsibilities

Applied AI & Agentic Solutions

• Build and enhance AI‑powered applications and agents that support real business workflows (e.g., document analysis, task delegation, knowledge retrieval, decision support).
• Implement agentic patterns such as tool‑calling, multi‑step reasoning, and workflow orchestration in collaboration with senior engineers.
• Develop and manage prompt strategies, prompt templates, and prompt evaluation techniques for reliability and reuse.
• Implement retrieval‑augmented generation (RAG) using enterprise data sources and vector databases.

Engineering & Production Readiness

• Help transition AI solutions from prototype to production, focusing on reliability, observability, and cost awareness.
• Package AI capabilities as APIs, services, or integrations consumable by other applications.
• Contribute to CI/CD pipelines and deployment patterns for AI applications (model updates, prompt changes, configuration).
• Monitor AI solutions in production and assist with troubleshooting performance, accuracy, or usability issues.

Data, Integration & Platform Collaboration

• Work with data engineers to integrate AI solutions with governed data sources (e.g., Fabric, Dataverse, SQL).
• Collaborate with platform teams on Azure‑based AI services, Copilot integrations, and Power Platform solutions.
• Support integration of AI into existing enterprise systems (ERP, content repositories, workflow tools).

Evaluation, Learning & Governance Awareness

• Participate in model and solution evaluation, including accuracy, latency, cost, and usability.
• Support testing and validation activities aligned with internal AI governance standards.
• Stay current with evolving AI tools, frameworks, and best practices and contribute ideas back to the team.
• Contribute to internal documentation, reusable patterns, and AI communities of practice.
• Perform other related duties as assigned.

Knowledge, Skills & Abilities

• Understanding of emerging standards for providing context to AI models, such as Model Context Protocol (MCP), and experience developing reusable "agent skills" to enhance model capabilities
• Familiarity with cloud platforms (Microsoft ecosystem (Azure/Fabric) preferred)
• Strong curiosity, learning velocity, and willingness to experiment responsibly
• Ability to communicate clearly with both technical and non‑technical partners
• Proficiency in designing, implementing, and troubleshooting AI solutions within enterprise environments.
• Ability to analyze and interpret complex data sets, applying statistical and machine learning techniques to derive actionable insights.
• Experience with integrating AI models into business processes, workflow tools, and content management systems.
• Knowledge of data governance, privacy, and ethical considerations in AI development and deployment.
• Competency in testing, validating, and monitoring AI models for performance, reliability, and compliance.
• Skill in preparing technical documentation and creating reusable frameworks or patterns for AI projects.
• Ability to collaborate effectively with cross-functional teams, including data engineers, platform specialists, and business stakeholders.
• Adaptability to rapidly evolving AI technologies, frameworks, and industry best practices.
• Strong problem-solving and critical thinking skills, with a focus on continuous improvement and innovation.
• Demonstrated ability to manage multiple projects or tasks concurrently, prioritizing effectively to meet deadlines.

Core Values

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