AI Platform Architect

Requirement/Must Have:

• 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.

Experience:

• 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 Google Cloud Platform 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.

Responsibilities:

• 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 Google Cloud Platform 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.

Should Have:

• 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.

Skills:

• Generative AI.
• Vertex AI.
• Gemini.
• Retrieval-Augmented Generation (RAG).
• Vector Embeddings.
• Vector Search.
• Google Cloud Platform (Google Cloud Platform).
• LangChain.
• Agentic AI.
• Model Context Protocol.
• MLOps.
• CI/CD.
• GitHub.
• Azure DevOps.
• Serverless Architecture.
• Container-Based Solutions.
• Cloud-Native Applications.
• Python.
• AI Architecture.
• Machine Learning Platforms.
• Data Pipelines.
• API Integrations.
• Agile Methodology.
• DevOps.
• Kubernetes.
• Docker.

Qualification and Education:

• 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.