Senior AI Architect

We need to output HTML fragment with sections: About the role? Actually the posting includes description: "Job Description" etc. We need headings for sections present: About the role? Not explicit. The posting includes "Job Description" with subsections: Client Architecture & Technical Leadership (~70%), Pre-Sales & Business Development (~30%), Knowledge Building & Mentoring. Also Qualifications, Additional Information includes Compensation & Benefits, Workplace, Work Authorization, Our Commitment (EEO). We must not include boilerplate like EEO etc. Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. So we should omit "Our Commitment" and "Work Authorization"? Work Authorization is not boilerplate but is a requirement; it's substantive. Should we include? It's a requirement about work authorization; it's not boilerplate. We can include maybe under a section "Requirements" or "Qualifications". But we have a Qualifications section already. We could incorporate work authorization into Qualifications as a bullet. However instructions: Use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we should map content to these standard headings where applicable. We have: - About the role: maybe a brief overview: "We are looking for an experienced Solution Architect to join our AI Platforms team..." That's the job description overview. Could be under About the role. - Responsibilities: includes Client Architecture & Technical Leadership (~70%), Pre-Sales & Business Development (~30%), Knowledge Building & Mentoring. - Requirements: Qualifications (Required) plus maybe Nice to Have as Skills? Or we could have Skills section for nice-to-have. - Qualifications: maybe we treat Required as Qualifications, Nice to Have as Skills. - Benefits: from Additional Information: Compensation & Benefits includes Base Salary range, Annual Performance Bonus, Medical, dental, vision, etc. Also Pay: we have base salary range. So we can have Pay section with salary range. Benefits section with list. - Schedule: Workplace mentions in-person collaboration, expected to work from office at least three days per week. Could be Schedule. We must not create sections with filler like "commensurate with experience". We have actual salary range, so Pay section is valid. We must not repeat job title as heading. Do not put Job ID/requisition numbers as headings. We must preserve ALL substantive information; do not invent or summarize away detail. So we need to include all details from the posting, but we can reorganize under headings. We need to output only HTML fragment, no /, no markdown fences. Let's extract details: Company intro: Sia is a next-generation, global management consulting group... etc. That's background; could be part of About the role or maybe a brief intro. We'll include as a paragraph under About the role. 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." Then responsibilities broken down: 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. Qualifications Required: - 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. Additional Information: Compensation & Benefits: - Compensation Base Salary: $117,300-$121,400 - Actual compensation within this range will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by applicable law. - Annual Performance Bonus - Benefits Medical, dental, and vision; company-paid life and AD&D; voluntary supplemental insurance and EAP - 401(k) with company match and immediate vesting; HSA and FSA options - College savings and student loan repayment programs - Paid parental leave; generous PTO, nine company holidays, and one floating holiday - Cell phone stipend; well-being and professional development programs - Benefits are subject to applicable plan terms and eligibility requirements. Workplace: - Sia values in-person collaboration. When serving clients, consultants may be required to work onsite at a client location based on engagement needs. - Between client engagements, consultants are expected to work from a Sia office or approved coworking location at least three days per week. - Candidates should reside within a reasonable commuting distance of a Sia office or approved coworking location. - Sia maintains offices and coworking arrangements across multiple U.S. markets, including New York City, Charlotte, Greater Seattle, San Francisco Greater Bay Area, Los Angeles, Houston, Atlanta, Baltimore, Chicago, Washington D.C. Work Authorization: - Applicants must be legally authorized to work in the United States at the time of application and throughout their employment. - This position is not eligible for employment visa sponsorship now or in the future. Our Commitment (EEO) - we should remove as boilerplate. Thus we need to produce sections: About the role, Responsibilities, Qualifications, Skills (nice-to-have), Benefits, Pay, Schedule, Work Authorization maybe as a separate section? The instruction list includes headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. It doesn't list Work Authorization but we could include under Requirements or Qualifications. Since it's a requirement, we could add to Qualifications or Requirements. Let's treat Requirements as a section for mandatory qualifications (including work authorization). Qualifications could be for preferred? But we already have Required and Nice to Have. To avoid duplication, we can map: - About the role: company intro + role overview paragraph. - Responsibilities: the three bullet groups. - Requirements: Required qualifications (Master's degree, years experience, deep expertise, etc.) plus work authorization and language fluency? Language fluency is also required. Could include. - Qualifications: maybe we treat as "Preferred Qualifications" (Nice to Have). But the instruction list includes Qualifications as a heading separate from Skills. Could use Qualifications for required, Skills for nice-to-have. However they also have Requirements heading. Might be confusing. Let's follow typical pattern: About the role, Responsibilities, Requirements (mandatory), Qualifications (preferred), Skills (technical skills), Benefits, Pay, Schedule. But we have both technical skills and soft skills. We'll allocate: - Requirements: education, years experience, deep expertise in at least two ecosystems, cloud architecture patterns, data/AI landscape, stakeholder engagement, communication, problem-solving, fluency in French & English, work authorization. - Qualifications: maybe we could include "Nice to Have" as Qualifications? Or we could treat Nice to Have as Skills. Let's decide: Skills heading for technical hands-on abilities, certifications, etc. Qualifications for preferred experience like management consulting, compliance frameworks. Thus: Requirements (mandatory): - Master’s degree in computer science, engineering, or related field. - 4 to 7 years experience in solution architecture, cloud architecture, or senior engineering role with significant design responsibilities. - Deep expertise in at least two of: AWS, Microsoft Azure, Google Cloud Platform, Databricks, OpenAI, Anthropic, NVIDIA. - Strong command of cloud architecture patterns — networking, security, compute, storage, managed AI/ML services. - Solid understanding of data and AI landscape: classical ML, deep learning, generative AI, autonomous agents, 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. - Legally authorized to work in the United States; no visa sponsorship. Skills (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. Benefits: list as above. Pay: Base Salary range $117,300-$121,400; Annual Performance Bonus. Schedule: Workplace expectations: in-person collaboration, onsite as needed, expected to work from Sia office or approved coworking location at least three days per week; reside within reasonable commuting distance; list of office locations. We must not include boilerplate like "Benefits are subject to applicable plan terms and eligibility requirements." That's okay to keep as it's substantive? It's a generic statement but still part of benefits