Senior Solution Architect
Role details
Job location
Tech stack
Job description
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%)
- 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%)
- 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.
Knowledge Building & Mentoring
- 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.
Requirements
- Master's degree in computer science, engineering, or a related field.
- 4 to 7 years of experience in solution architecture, cloud architecture, or a 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 solutions.
- Excellent communication and presentation skills - able to convey complex technical concepts to both technical and non-technical audiences.
- Strong problem-solving skills and ability to make sound architectural trade-offs under uncertainty.
- Fluent in French; professional proficiency in English.
Nice to Have
- Hands-on coding ability (Python, Terraform/IaC, or similar) for prototyping and technical validation.
- Experience with MLOps / LLMOps tooling and production deployment pipelines.
- Professional-level certifications (e.g., AWS Solutions Architect Professional, Azure Solutions Architect Expert, Google Cloud Professional Cloud Architect, Databricks Professional Data Engineer).
- Experience in management consulting or client-facing delivery environments.
- Familiarity with AI compliance frameworks and responsible AI practices.