Overview
As an Enterprise AI Architect, you will design and lead the implementation of enterprise-scale Generative AI solutions. You’ll define AI architectures, establish technical standards, and build secure, scalable platforms leveraging LLMs, Agentic AI, and RAG to solve complex business challenges.
Your Role and Responsibilities
- Design and implement enterprise-grade Generative AI architectures from concept through production deployment.
- Lead the architecture and implementation of LLM, Agentic AI, and Retrieval-Augmented Generation (RAG) solutions.
- Define architecture standards, technical guidelines, and best practices for enterprise AI platforms.
- Design scalable AI ecosystems integrating cloud platforms, APIs, enterprise applications, and business workflows.
- Define AI governance, security, observability, Responsible AI, and LLMOps best practices.
- Design knowledge retrieval architectures using embeddings, vector databases, semantic search, chunking, and ranking strategies.
- Evaluate and recommend AI technologies, frameworks, and cloud services based on business and technical requirements.
- Collaborate with engineering, architecture, security, and business teams to translate business needs into scalable AI solutions.
- Provide technical leadership throughout the solution lifecycle, from architecture through production deployment.
- Create and maintain architecture documentation, technical standards, and implementation guidelines.
REQUIREMENTS
- Experience in Software Architecture, Solution Architecture, AI Architecture, or Enterprise Architecture.
- Hands-on experience designing enterprise Generative AI solutions using Large Language Models (LLMs).
- Experience designing and implementing Agentic AI and Retrieval-Augmented Generation (RAG) architectures.
- Experience with enterprise AI platforms such as Azure AI Foundry, Azure OpenAI, AWS Bedrock, Vertex AI, or OpenAI Enterprise.
- Strong understanding of embeddings, vector databases, semantic search, chunking, ranking, and knowledge retrieval architectures.
- Experience designing secure, scalable, production-ready AI solutions.
- Knowledge of AI governance, Responsible AI, observability, prompt lifecycle management, and LLMOps.
- Experience integrating AI solutions with enterprise APIs, cloud platforms, and business applications.
- Hands-on experience with AI frameworks such as LangChain, LangGraph, CrewAI, Semantic Kernel, AutoGen, OpenAI Agents, or similar.
- Strong communication skills with experience collaborating with technical leadership and business stakeholders.
- Advanced English communication skills (client-facing environment).
Working at Motivus
What Working Here Looks Like
- Opportunities for professional growth and career development.
- Work on strategic, high-impact enterprise AI initiatives.
- Exposure to cutting-edge AI technologies, cloud platforms, and modern engineering practices.
- Collaborative, innovative, and knowledge-sharing environment.
- Continuous learning through technical communities, certifications, and professional development programs.
- Opportunity to work with global clients that are leaders in their industries.
OUR VALUES
Culture of Innovation: We relentlessly pursue innovation, empowering our teams to explore new ideas, emerging technologies, and creative solutions.
Responsibility: We strive to create a positive impact for our clients, our colleagues, and the communities we serve through accountability and collaboration.
Learning & Development: We foster a culture of continuous learning, encouraging our people to grow professionally, share knowledge, and lead with expertise.
At Motivus, we are committed to equal opportunity and value diversity and inclusion in our workplace. We believe that different perspectives strengthen our teams, foster innovation, and help us build better solutions for our clients.
