AI Solutions Architect
You will be primarily focusing on the earlier stages of the software development life cycle, you will collaborate with our Portfolio Delivery function to understand customer and technical needs and design architectural solutions to meet them that are innovative, scalable, reusable and aligned with the company's technology standards and conventions
Following project approval, you will form part of the Pod Leadership team tasked with bringing your architectural vision to fruition utilising agile methodologies. You will elaborate your architecture designs and collaborate with our infrastructure and development teams to enable implementation of them with light touch oversight.
Successful candidates will possess the following AI competency's:
- AI Evolution & Business Impact: Analyze the evolution of AI technology and its implications for business strategies to identify opportunities for innovation and efficiency.
- AI Governance, Security, Compliance, and Ethics: Ensure compliance with AI governance frameworks, focusing on bias detection, data privacy, and regulations (eg, GDPR, HIPAA).
- Generative AI, LLMs, NLP, & Computer Vision: Utilize generative AI and large language models (LLMs) to create intelligent applications, with knowledge of models like GPT and Gemini, prompt engineering, and RAG integration.
- AI-Augmented Development Engineering: Integrate AI tools into the software development life cycle to enhance coding practices and code reviews (eg, GitHub Copilot).
- Agentic AI & Autonomous Systems: Design autonomous systems using agentic AI to automate tasks and improve operational efficiency.
- Cloud AI & ML Services: Utilize AI and ML services from major cloud platforms (AWS, Azure, Google Cloud) to build scalable, intelligent applications, including model training and deployment.
- Machine Learning (ML) & Deep Learning (DL) Fundamentals: Apply ML and DL principles to design data-driven solutions that enhance business processes.
- Continuous Learning & Collaboration: Stay open to learning about emerging AI tools and methodologies while collaborating effectively with data architects, AI engineers, and technical experts to design and implement intelligent solutions that meet business needs.
This is a fully remote assignment outside of IR35 (UK Based)
Reference: 2945226696
AI Solutions Architect

Posted on May 8, 2025 by Sterling Manhattan
You will be primarily focusing on the earlier stages of the software development life cycle, you will collaborate with our Portfolio Delivery function to understand customer and technical needs and design architectural solutions to meet them that are innovative, scalable, reusable and aligned with the company's technology standards and conventions
Following project approval, you will form part of the Pod Leadership team tasked with bringing your architectural vision to fruition utilising agile methodologies. You will elaborate your architecture designs and collaborate with our infrastructure and development teams to enable implementation of them with light touch oversight.
Successful candidates will possess the following AI competency's:
- AI Evolution & Business Impact: Analyze the evolution of AI technology and its implications for business strategies to identify opportunities for innovation and efficiency.
- AI Governance, Security, Compliance, and Ethics: Ensure compliance with AI governance frameworks, focusing on bias detection, data privacy, and regulations (eg, GDPR, HIPAA).
- Generative AI, LLMs, NLP, & Computer Vision: Utilize generative AI and large language models (LLMs) to create intelligent applications, with knowledge of models like GPT and Gemini, prompt engineering, and RAG integration.
- AI-Augmented Development Engineering: Integrate AI tools into the software development life cycle to enhance coding practices and code reviews (eg, GitHub Copilot).
- Agentic AI & Autonomous Systems: Design autonomous systems using agentic AI to automate tasks and improve operational efficiency.
- Cloud AI & ML Services: Utilize AI and ML services from major cloud platforms (AWS, Azure, Google Cloud) to build scalable, intelligent applications, including model training and deployment.
- Machine Learning (ML) & Deep Learning (DL) Fundamentals: Apply ML and DL principles to design data-driven solutions that enhance business processes.
- Continuous Learning & Collaboration: Stay open to learning about emerging AI tools and methodologies while collaborating effectively with data architects, AI engineers, and technical experts to design and implement intelligent solutions that meet business needs.
This is a fully remote assignment outside of IR35 (UK Based)
Reference: 2945226696

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