Power Platform & Extensibility: Design appropriate use of Power Apps, Power Automate, Power BI, Copilot Studio, Dataverse, custom connectors, APIs, and Azure services where standard Dynamics capabilities need to be extended.
Integration & Data Architecture: Define integration approaches between Dynamics 365, telephony services, customer platforms, data sources, reporting services, and wider enterprise systems, ensuring resilient and maintainable designs.
Governance & Best Practice: Establish solution design standards, review low-level designs, support fit-gap analysis, manage technical risks, and ensure adherence to Microsoft implementation guidance and platform best practices.
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We are hiring for one of our clients, seeking a Enterprise Client Partner (Frontier AI) to work on a full-time basis. This individual will engage deeply with research, engineering, and procurement stakeholders to drive high-value partnerships around model evaluation and human data solutions. The Enterprise Client Partner will source and close partnerships with AI labs and ML-driven organizations working on frontier models, leveraging their expertise to improve model performance. This role will play a crucial part in shaping the future of AI, working with global leaders in the technology and engineering industries.
Lead and influence multi-disciplinary teams in implementing and operating cyber security controls for cloud and on-premises environment; micro-services, containers, applications, operating systems, databases, and networks.
Provide recommendations for the configuration and improvement of security detection and response tools (e.g. SIEM, VA, NDR, XDR, EDR, etc) to enhance operational effectiveness.
Evaluates new technologies and validate the security of the technology including lab setup and proof of concepts (PoC).
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Lead the design of AI and agentic architectures that combine data pipelines, large language models (LLMs), and reasoning engines.
Use frameworks such as LangChain, LlamaIndex, and Retrieval-Augmented Generation (RAG) to enable contextual, autonomous AI applications.
Leverage hyperscaler ecosystems including Google Gemini, Agentspace, AWS Bedrock, and Azure AI Studio to operationalize next-generation AI systems.
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