About The Position

Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. Solvd Cloud, Infra, Data & Security is growing fast, and our architecture leadership needs to keep up. We need someone who can take an unclear problem, define it, design the answer, and make sure it ships. You'll set technical direction across cloud, infrastructure, and data. You'll shape engagements and roadmaps before they're committed. And you'll stay close enough to delivery that what we design is what gets built. We operate AI-first: you'll use AI as a daily tool to move faster and multiply what you and the teams around you can deliver. There will be ambiguity. That's the job. The plans don't exist yet, and you'll help write them.

Requirements

  • 12+ years in infrastructure, cloud, or data engineering, including several years as the accountable architect for production systems at scale.
  • Deep hands-on experience with AWS and/or Azure, production Kubernetes, and Terraform (or an equivalent IaC tool).
  • Experience designing and shipping modern data platforms (e.g., Databricks, Snowflake, Fabric, Redshift), including governance and data quality.
  • Security-first mindset: IAM design, zero-trust networking, encryption, and audit readiness are defaults.
  • Experience using AI as a force multiplier, with concrete examples of AI shortening delivery timelines or expanding output, and understanding its limitations.
  • Ability to explain tradeoffs to executives and debug with engineers.
  • Ability to act under ambiguity and write the first draft of plans, adjusting as learning occurs.

Nice To Haves

  • Experience putting GenAI or LLM systems into production (RAG, evaluation, guardrails, agent orchestration).
  • Multi-cloud or hybrid experience at enterprise scale.
  • Experience in regulated industries such as financial services, healthcare, or the public sector.
  • AWS Solutions Architect Professional, Azure Solutions Architect Expert, or CKA certifications.
  • Experience building an architecture practice or center of excellence from an early stage.

Responsibilities

  • Define reference architectures, landing zones, and standards across AWS and Azure, Kubernetes, and infrastructure-as-code.
  • Design lakehouse and warehouse, streaming, and governance patterns for data and AI platforms.
  • Design the platform layer that moves GenAI and agentic workloads from prototype to production, covering access control, evaluation, observability, and cost guardrails.
  • Lead technical discovery, size and de-risk work, and write solution designs and technical scope that teams commit to.
  • Use AI tools across the architecture lifecycle: discovery synthesis, design drafts, IaC and code generation, review, documentation, and estimation.
  • Turn what works into repeatable patterns and prompts the team adopts, and set guardrails for AI usage with client and production data.
  • Own IAM, network segmentation, secrets management, and logging, ensuring designs meet security and compliance standards.
  • Ensure every design includes a run cost, reliability targets, an observability plan, and a rollback path.
  • Run design reviews, mentor architects and senior engineers, and turn repeat solutions into reusable accelerators.

Benefits

  • Continuous learning
  • Innovation
  • Ethical AI standards
  • Global team collaboration
  • Equal opportunities
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