Solution Architect AI

Solution Architect AI

Santa Clara, CA 95054 (Onsite)

Full-Time

As an AI Solution Architect, you will define and deliver the technical blueprint for AI connectors, agent workflows, and integration patterns needed to operationalize Gemini Enterprise (Agentspace) solutions. Work closely with architects, developers, and enterprise stakeholders to ensure technical clarity and high‑quality implementation.

Experience / Skills

·                     8–12 years of experience in solution architecture, cloud engineering, or enterprise integration with strong hands‑on AI delivery exposure

·                     3–5 years: Hands‑on experience designing ingestion connectors, action connectors, schema mapping, field‑level policies, normalization, and validation frameworks

·                     Experience with Vertex AI, Cloud Run, Cloud Functions, IAM, Secret Manager, API Gateway, Terraform, Cloud Build CI/CD

·                     Experience integrating multi‑agent pipelines, context models, session identifiers, OBO flows, and service‑to‑agent interactions

·                     Hands‑on experience implementing retrieval, embeddings, hybrid search, validation rules, error handling, idempotency, and testing frameworks

·                     5+ years: Building secure, resilient, production‑grade microservices with structured logging, retries, backoff, correlation IDs

·                     Secondary Skills - Knowledge of MCP’s and A2A SDK; Proficiency with Version Control tools like Git; Experience in Agile Methodologies/ development environments

·                     Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or equivalent

Key Responsibilities

·                     Lead design workshops with client teams to define connector schemas, mapping matrices, and action specifications

·                     Architect and document High‑Level Designs (HLDs), low‑level specifications, error taxonomies, authentication/authorization flows, and NFRs

·                     Develop patterns for OBO/OAuth2 integration, identity propagation, and secure service communication

·                     Provide end‑to‑end design guidance for microservices, ingestion pipelines, grounding workflows, and action connectors

·                     Support developers during build cycles and ensure adherence to design specifications

·                     Troubleshoot integration issues, optimize API performance, and validate data/semantic grounding quality

·                     Support testing: unit tests, integration validation, UAT sign‑off, and production rollout

·                     Prepare deployment guides, runbooks, configuration documents, and post‑deployment knowledge transfers

·                     Strong client‑facing communication and clarity in explaining technical decisions; Collaborative, solution‑oriented, flexible under changing requirements

·                     Ability to lead design walkthroughs and drive alignment across teams; Detail‑oriented, structured, and dependable execution style

·                     Communicate effectively with internal and customer stakeholders; Communication approach: verbal, emails and instant messages

·                     Strong interpersonal skills to build and maintain productive relationships with team members & customer representatives

·                     Provide constructive feedback during code reviews and be open to receiving feedback on your own code

·                     Analytical mindset; Ability to bring idea into reality thought technology implementation & adoption

·                     Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps

·                     Problem-Solving and Analytical Thinking; Capability to troubleshoot and resolve issues efficiently

·                     Provides regular updates, proactive and due diligent to carry out responsibilities

Expected Outcome

·                     Production‑ready ingestion and action connectors delivered with expected SLAs

·                     Fully documented architecture, mapping matrices, integration patterns, and CI/CD assets

·                     Seamless end‑to‑end integration with Gemini Agentspace and downstream systems

·                     Stable, secure, and performant AI agent workflows