Solution Architect

Job Overview We are seeking an experienced Senior Solution Architect to join our GenAI and DevOps practice. The ideal candidate combines strong cloud infrastructure expertise (with a primary focus on Google Cloud Platform, alongside AWS and Azure) with hands-on experience building and deploying GenAI solutions — including Gemini Enterprise, Vertex AI, and agent-based architectures. The candidate should be equally comfortable designing Kubernetes-based infrastructure and CI/CD pipelines as they are architecting AI agent workflows, RAG pipelines, and LLM-powered applications for enterprise clients. Key Responsibilities Cloud & DevOps Lead cloud migration projects from on-premises or other cloud platforms to GCP (primary), AWS, or Azure. Design and implement migration strategies ensuring minimal downtime and maximum efficiency. Design, implement, and optimize CI/CD pipelines to streamline software delivery. Use Terraform for infrastructure as code (IaC) to automate deployment processes. Architect and optimize Kubernetes (GKE) clusters for high availability and scalability. Design scalable database architectures and execute migrations with a focus on data consistency, integrity, and performance. AI / GenAI Architect and deploy GenAI solutions on GCP, including Gemini Enterprise rollouts, Vertex AI Search, and Vertex AI Agent Builder (ADK) implementations. Design and build AI agents and multi-agent systems, including integrations via MCP (Model Context Protocol) with enterprise systems (CRM, ERP, ticketing, document stores). Build RAG (Retrieval-Augmented Generation) pipelines and conversational analytics solutions on enterprise data (e.g., BigQuery Conversational Analytics). Evaluate and architect migrations from other LLM providers (e.g., OpenAI) to Vertex AI/Gemini, including TCO analysis. Work with speech and multimodal AI pipelines (STT, TTS, multilingual/multimodal agents) where relevant to client use cases. Client & Leadership Work closely with clients to assess architectures, define scope, and produce technical SOWs/proposals across both DevOps and AI engagements. Provide technical leadership and mentorship to junior team members. Stay current with GCP's evolving AI/ML and infrastructure tooling and bring emerging capabilities into client solutions. Required Skills and Qualifications Bachelor's degree in Computer Science, Information Technology, or related field. 7+ years of relevant industry experience, including experience in a Solution Architect role. Strong hands-on experience with GCP (required); working knowledge of AWS and Azure. Expertise in DevOps practices: CI/CD pipelines, Terraform/IaC, Kubernetes/GKE. Practical experience with GenAI on GCP: Vertex AI, Gemini models, Agent Builder/ADK, or comparable platforms. Experience integrating AI agents with enterprise systems (APIs, MCP, or similar integration patterns). Sound knowledge of database migrations and data pipeline design. Excellent communication skills, with the ability to articulate complex technical and AI concepts to both technical and non-technical stakeholders.