AI Architect

Location: Noida, India

Department: Data Science

Experience: 10+

Skills: Microservices, Data Science, Cloud, Data Analytics, Agentic AI, AI Engineering, Data Engineering, Platform Engineering

• Own end-to-end technical architecture across all tracks, aligned to Google Cloud standards, APIs, and roadmap.
• Define and enforce engineering best practices, coding standards, and review processes across all workstreams.
• Make high-stakes decisions on data modeling, pipeline architecture, schema design, and system integration — with clear documentation.
• Identify technical risks and cross-track conflicts early; drive resolution before they impact delivery.
• Lead architecture review sessions with Google's core engineering team.

• Serve as the single technical point of contact horizontally across all tracks, ensuring consistent patterns and interfaces.
• Facilitate technical syncs across track leads; surface dependencies early and coordinate sequencing of deliverables.
• Define shared standards for data contracts, API interfaces, and infrastructure configuration.

• Build and maintain a strong working relationship with the Google Cloud core team through joint ceremonies, reviews, and design discussions.
• Represent CLOUDSUFI's delivery quality and technical credibility in all Google interactions.
• Translate complex technical discussions into clear summaries for both technical and non-technical audiences.
• Proactively communicate progress, blockers, and decisions to CLOUDSUFI leadership and Google program managers.

• Drive code reviews, set quality gates, and ensure CI/CD, test coverage, and observability standards are met across tracks.
• Champion performance, reliability, and scalability from design through production.
• Mentor and technically grow senior engineers across tracks (without formal HR responsibility).
• Contribute hands-on to critical technical work — this is a hybrid IC and leadership role.

• Google Cloud — knowledge graph, Gemini, import pipelines, and the Statistical Variable hierarchy.
• Google Cloud Spanner — schema design, distributed transactions, interleaved tables, and performance tuning at scale.
• Google BigQuery — data modeling, partitioning/clustering, query optimization, and downstream integration.
• Data pipelines — Apache Beam / Dataflow or equivalent GCP-native ETL tooling.
• Infrastructure as Code — Terraform on GCP; Cloud Build, Artifact Registry, GKE or Cloud Run.

• Python — primary language for Cloud import tooling and ML pipelines.
• TypeScript / React — Cloud web frontend and visualization layers.
• ML lifecycle — Vertex AI, BigQuery ML, or equivalent.
• Knowledge graphs — RDF / SPARQL or statistical data modeling; Cloud Python / REST APIs and DCID import automation.
• Google engineering culture — familiarity with internal tools (Buganizer, Critique, Cider) or prior delivery inside a Google product or partnership engagement.

• 10+ years of software engineering experience, including 3+ years as a formal or informal tech lead across multiple workstreams.
• Demonstrable experience delivering production-grade systems on Google Cloud Platform.
• Prior experience working with or for Google (as a Googler, through a partnership program, or embedded as a contractor) — strongly preferred.
• Exceptional verbal and written English; able to engage confidently with senior Google engineers and program managers.
• Proven ability to operate across ambiguous, fast-moving programs with multiple parallel tracks.
• Based in Guadalajara, Mexico, and able to collaborate on-site as required by the engagement.

• Experience in data and AI consulting or professional services, particularly within the Google Cloud partner ecosystem.
• Familiarity with open data, public statistics, or knowledge graph use cases (UN SDG data, census, health/economic indicators).
• Prior contribution to open-source projects, particularly Google Cloud or related tooling.

• A flagship engagement at the intersection of Google's open data infrastructure and real-world AI/data impact.
• Daily collaboration with Google's core engineering team on a strategic open data initiative.
• Competitive compensation benchmarked at Principal level in the Guadalajara market.
• CLOUDSUFI's full benefits package.
• A culture that values technical excellence, client trust, and a people-first approach to delivery.