AI Platform Architect

Generative AI Solutions Architect

Strong production experience delivering Generative AI applications in enterprise or customer-facing environments.

Deep hands-on expertise with Google Cloud Platform Vertex AI and Gemini models.

Strong experience designing and implementing Retrieval-Augmented Generation (RAG) architectures.

Experience building vector embedding pipelines and vector search solutions.

Strong cloud-native architecture and deployment experience.

Experience designing scalable AI and machine learning platforms.

Strong understanding of data grounding strategies and vector database architectures.

Experience building serverless or container-based cloud solutions.

Strong communication, analytical, and problem-solving skills.

Experience working in Agile software development environments.

8+ years of experience in software development or engineering roles.

Experience delivering enterprise-grade Generative AI applications into production.

Hands-on experience with Vertex AI Studio and GCP AI services.

Experience building data pipelines for embedding and vector storage solutions.

Experience with CI/CD and MLOps tooling.

Experience with DevOps tools such as GitHub or Azure DevOps.

Experience with AI frameworks such as LangChain preferred.

Experience with Model Context Protocol concepts preferred.

Experience with Agentic AI and autonomous systems preferred.

Experience integrating AI platforms with CRM, ERP, eCommerce, EMR, or EHR systems preferred.

Experience with serverless and containerized cloud architectures.

Experience leading proof-of-concept and proof-of-technology initiatives.

Lead the design, development, and implementation of enterprise-grade Generative AI solutions on Google Cloud Platform.

Architect and implement advanced Retrieval-Augmented Generation (RAG) systems.

Design and build scalable vector embedding and vector search pipelines.

Develop data grounding strategies to connect LLMs with enterprise and real-time data sources.

Implement AI architectures using Vertex AI, Gemini, and related GCP services.

Explore and implement Agentic AI concepts for autonomous reasoning and task execution.

Support implementation of Model Context Protocol integrations for external tool connectivity.

Collaborate with business stakeholders, architects, developers, and project teams to gather requirements and deliver AI solutions.

Lead technical investigations and provide solution recommendations for complex AI initiatives.

Guide engineering teams in effort estimation, forecasting, and technical execution.

Conduct proof-of-concept and proof-of-technology activities for AI platform initiatives.

Promote Agile practices and collaborate across cross-functional teams.

Ensure scalability, security, reliability, and maintainability of AI platforms.

Support CI/CD and MLOps implementation for AI and machine learning workflows.

Communicate technical concepts effectively to technical and non-technical stakeholders.

Growth mindset and willingness to learn emerging AI technologies.

Strong leadership and collaboration abilities.

Excellent verbal and written communication skills.

Ability to simplify and explain complex technical concepts.

Strong stakeholder management skills.

Ability to work in fast-paced enterprise environments.

Strong focus on innovation and continuous improvement.

Bachelor’s degree in Computer Science or related field required.

Advanced certifications or cloud certifications preferred.

Equivalent combination of education and relevant experience may be considered.