Senior Solution Architect

Sia is a next-generation, global management consulting group. Founded in 1999, we were borndigital. Today our strategy and management capabilities are augmented by data science, enhanced by creativityand driven by responsibility.We're optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertisedelivers results. Our optimism transforms outcomes.

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Sia's AI Platforms Business Unit designs, builds and scales the data and AI platforms that power enterprise transformation. From cloud infrastructure to machine learning pipelines, from generative AI applications to autonomous agents, our teams deliver end-to-end solutions that move from proof‑of‑concept to production at scale. By joining AI Platforms, you step into an environment where technical depth meets business impact — and where your architectural decisions shape how organizations adopt AI responsibly and effectively.

We are looking for an experienced Solution Architect to join our AI Platforms team. In this role, you will be the technical authority on client engagements — translating complex business requirements into robust, scalable data and AI architectures across cloud, machine learning, and generative AI domains.

You will work directly with senior client stakeholders (CIO, CISO, Engineering leads) to define technical vision, remove impediments for delivery teams, and ensure that architectural choices align with security, compliance, and cost constraints. You will also contribute to pre‑sales activities by scoping solutions, estimating effort, and building technical proposals that win new business.

This is a staff‑level individual contributor role embedded part‑time in cross‑functional project teams, with a clear path toward engineering management for those who choose it.

Responsibilities

Client Architecture & Technical Leadership (~70%)

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• Define and own the end‑to‑end technical architecture for data and AI projects — covering cloud infrastructure, data pipelines, ML/DL model serving, generative AI applications, and agent‑based systems.
  
• Act as the primary technical point of contact for client stakeholders, aligning architectural decisions with business objectives, security policies, and regulatory requirements (GDPR, EU AI Act).
  
• Lead architecture reviews, design sessions, and technical governance forums to ensure quality and coherence across workstreams.
  
• Remove technical impediments for engineering teams and provide hands‑on guidance when needed.
  
• Oversee the full project lifecycle: from advisory and assessments through prototyping (POC/MVP) to full‑scale production deployment.
  
• Ensure solutions are designed for production readiness — addressing scalability, reliability, observability, and cost optimization.
  

Pre‑Sales & Business Development (~30%)

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• Support business development by contributing to technical scoping, architecture proposals, and effort estimations during the sales cycle.
  
• Participate in client presentations and workshops to demonstrate Sia's technical capabilities and build trust.
  
• Identify expansion opportunities within existing accounts by surfacing new use cases and technical needs.
  
• Mentor junior consultants and engineers, helping them grow their architectural thinking and client‑facing skills.
  
• Contribute to building internal IP, accelerators, and reference architectures that leverage frontier technological developments.
  
• Stay current on the evolving landscape of cloud services, AI frameworks, and industry best practices.
  

Qualifications

Required

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• Master's degree in computer science, engineering, or related field.
  
• 4 to 7 years of experience in solution architecture, cloud architecture, or senior engineering role with significant design responsibilities.
  
• Deep expertise in at least two of the following technology ecosystems: AWS, Microsoft Azure, Google Cloud Platform, Databricks, OpenAI, Anthropic, NVIDIA.
  
• Strong command of cloud architecture patterns — networking, security, compute, storage, and managed AI/ML services.
  
• Solid understanding of the data and AI landscape: classical ML, deep learning, generative AI, autonomous agents, and data engineering.
  
• Proven ability to engage with senior client stakeholders (CIO, CISO, VP Engineering) and translate business needs into technical soluti