• Configure and maintain platform environments across TMS platforms (e.g., XTM, Phrase, memoQ, Trados), including MT engine connections, workflows, AIPE/AIQE parameters, and provider-level settings (glossaries, dictionaries, model selection). • Act as the primary diagnostics layer between production teams and AI/ML Engineering. Investigate MT quality issues, identify root causes (data, engine, pipeline, or TMS), and escalate with clear reproduction steps and context. • Manage end-to-end MT operations: data preparation, TM analysis, engine training, evaluation, deployment, and monitoring. Maintain relationships with MT providers and identify opportunities to optimise performance. • Support pre-sales as an MT/AI subject matter expert. Build ROI models, prepare QBR insights (e.g., edit distance trends, MT savings, cost usage), and advise clients on MT strategy, including engine selection and content suitability. • Identify and eliminate manual processes through automation. Design or build tools, scripts, and workflows that reduce human intervention and improve scalability. This is a core expectation of the role.

• Design and build the core infrastructure for the Agent Platform • Own the platform APIs, orchestration layers, and runtime systems for AI agents • Develop the marketplace for deploying autonomous intelligence • Collaborate with cross-functional teams to enhance the platform

• Architect agents that don't just answer questions but do work • Give agents secure, governed access to the systems and data they need to act • Design, build, and deploy MCP servers across two tracks • Build the OAuth and credential management layer • Work with R&D Architecture to define production-ready standards for Placer MCP server • Triage incoming connector requests and bug reports from across the company • Build and maintain Cowork plugins and Claude skills • Take ownership of Placer's internal BI environment on Databricks • Build and maintain tooling to track internal AI tools usage • Optimize compute, storage, and networking across the internal AI platform • Implement security best practices for AI platforms

• Configure, customize, extend, and support Dynamics 365 CRM and Dataverse solutions. • Design, build, deploy, and support custom Dynamics 365 functionality. • Design, build, enhance, and support customer-facing Power Pages portal capabilities. • Develop and maintain Power Automate flows, Power Apps, Dataverse components, and reusable platform patterns. • Support and extend the organization’s Microsoft-supported Business Central and Dataverse/Dynamics integration patterns. • Design, troubleshoot, and support API-driven integrations. • Identify opportunities to expand the practical use of CRM across various workflows. • Support clear solution management, environment promotion, deployment practices, documentation, testing, and governance. • Troubleshoot defects, monitor system behavior, and improve system performance.