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Senior Manager, Solutions Architecture - Data & AI
Высокая оценка обусловлена престижем компании TELUS, возможностью работать с передовыми технологиями (Agentic AI, LLM) и гибким форматом работы (Remote/Hybrid). Роль предлагает отличный баланс между стратегией и архитектурой.
Сложность вакансии
Роль требует редкого сочетания глубоких технических знаний в области AI/ML и развитых навыков пресейла и консалтинга. Кандидат должен уметь не только проектировать сложные системы, но и вести коммерческие переговоры на уровне топ-менеджмента.
Анализ зарплаты
Указанный диапазон соответствует рыночным стандартам США для позиций уровня Senior Manager в сфере Solutions Architecture с фокусом на AI и Data. В крупных технологических хабах и консалтинговых компаниях уровня Tier-1 зарплаты могут достигать верхней границы диапазона за счет бонусов.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Manager, Solutions Architecture position at TELUS Digital. With a robust background in architecting scalable data ecosystems and a deep focus on AI/ML methodologies, I am confident in my ability to bridge the gap between complex technical requirements and strategic business objectives. My experience spans across major cloud platforms including AWS and Azure, with specific expertise in implementing Databricks and Snowflake solutions that drive transformative results.
Throughout my career in client-service environments, I have excelled at leading technical discovery and scoping for high-stakes projects. I am particularly drawn to TELUS Digital’s 'people-first' culture and your commitment to end-to-end digital transformation. I am eager to bring my expertise in MLOps and Agentic AI to your team, helping to refine data products and provide the technical leadership necessary to deliver seamless, digitally-powered experiences for your global clientele.
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Описание вакансии
Who We Are
Welcome to TELUS Digital— where innovation drives impact at a global scale. As an award-winning digital product consultancy and the digital division of TELUS, one of Canada’s largest telecommunications providers, we design and deliver transformative customer experiences through cutting-edge technology, agile thinking, and a people-first culture.
With a global team across North America, South America, Central America, Europe, Africa, and APAC, we offer end-to-end expertise across eight core service areas: Digital Product Consulting, Digital Marketing Services, Data & AI, Strategy Consulting, Business Operations Modernization, Enterprise Applications, Cloud Engineering, and QA & Test Engineering.
From mobile apps and websites to voice UI, chatbots, AI, customer service, and in-store solutions, TELUS Digital enables seamless, trusted, and digitally powered experiences that meet customers wherever they are — all backed by the secure infrastructure and scale of our multi-billion-dollar parent company.
Location & Flexibility
This role will be in a Work From Near (Hybrid) capacity based in one of the following offices: Boston, MA, Columbus, OH, Charlottesville, VA, or Durham, NC, OR in a Work From Anywhere (Remote) capacity with travel to clients and TELUS Digital Solutions offices expected.
The Opportunity
As a Senior Manager, Solutions Architecture with a focus on Data & AI, you'll play a pivotal role in bridging the gap between pre-sales strategy and project delivery. Drawing on your deep knowledge of data ecosystems, machine learning, and AI technologies, you'll help shape, architect, and launch impactful solutions that align with client and executive partner goals. Whether leading architectural discovery for new data and AI initiatives or guiding in-flight projects, you'll ensure solutions are both technically sound and aligned with business objectives and operational needs.
You'll engage with prospective clients to explore how our capabilities can meet their unique data and AI challenges, lead architecture efforts for new engagements, and collaborate closely with delivery teams to bring client visions to life. You'll also provide critical estimates around team composition, build scope, and resource planning—ensuring data and AI projects are realistically scoped and staffed for success.
Between engagements, you'll lend your expertise across teams as a flexible problem-solver, while deepening your knowledge in areas like cloud data platforms (e.g., Databricks, Snowflake, Azure, AWS, GCP) or advanced AI/ML methodologies.
Responsibilities
- Presale: Lead scoping, technical design, and work planning during the presale process, articulating our data and AI capabilities to prospective clients.
- Delivery: Play the lead role in technical architecture and discovery projects, using consulting methods to refine the data product and technical architecture of client projects. This includes designing scalable data pipelines, machine learning model architectures, and MLOps frameworks.
- Subject Matter Expertise: Own a "technology vertical" within Data & AI, encompassing solution design, platform selection (e.g., Databricks, Snowflake, AWS Bedrock), implementation support, and thought leadership. This may include areas such as large-scale data warehousing, real-time analytics, machine learning operations (MLOps), or agentic AI systems.
- Roving Catalyst: Enhance existing project teams with architectural account-level guidance or specific subject matter expertise in data engineering, machine learning, or artificial intelligence.
Qualifications
- Multi-platform familiarity, with expertise in one or more of the following:
+ Cloud Data Platforms: Deep experience with Databricks, Snowflake, or other major cloud data warehousing/lakehouse solutions.
+ Cloud AI/ML Services: Proficiency with cloud-native AI/ML platforms (e.g., AWS Bedrock / Sagemaker, Azure ML, Google AI Platform/Vertex AI).
+ Backend Cloud Platforms: Strong experience with major cloud providers (AWS, Azure, GCP) for deploying and managing data and AI solutions.
- Data & AI Industry Expertise: Specialized knowledge of the data ecosystem, including data ingestion, ETL/ELT processes, data warehousing, data lakes, and real-time analytics.
- Machine Learning & AI Acumen: Candidates should be aware of current trends in machine learning (supervised, unsupervised, deep learning), MLOps, and advanced AI concepts like Agentic AI or Large Language Models (LLMs).
- Technical Proficiency:
+ Deep understanding of MLOps principles and tools for continuous integration/continuous delivery (CI/CD) of machine learning models.
+ Familiarity with containerization (Docker) and orchestration (Kubernetes) for scalable deployments.
- Experience with software estimation, work planning, and building project plans within time/cost constraints.
- An eye for details and an ability to navigate ambiguity.
- Experience delivering software or data solutions in an agency/client-service environment.
- Ability to clearly break down complex data and AI concepts to both technical and non-technical individuals, including executive stakeholders.
- Experience in having commercial conversations involving budgets and fees related to data and AI initiatives.
- Passion to apply modern processes that transform client organizations (e.g., continuous delivery, rapid iteration, and agile-inspired methodologies for data and ML).
- Excellent verbal and written communication skills.
- Ability to use repeatable frameworks and best practices to incorporate new data technologies or AI concepts.
- Appreciation for the wider client enterprise, beyond a single data project or AI initiative, and a desire to expand an account to service a client holistically.
- Equally comfortable working in pre-sale and post-sale environments.
Equal Opportunity Employer
At TELUS Digital, we are proud to be an equal opportunity employer and are committed to creating a diverse and inclusive workplace. All aspects of employment, including the decision to hire and promote, are based on applicants’ qualifications, merits, competence and performance without regard to any characteristic related to diversity.
We will only use the information you provide to process your application and to produce tracking statistics. Since we do not request personal data deemed sensitive, we ask you to abstain from sharing that information with us.
For more information on how we use your information, see ourPrivacy Policy.
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Навыки
- Agile
- LLM
- Kubernetes
- MLOps
- Docker
- Snowflake
- Databricks
- ETL
- Data Warehousing
- Google Vertex AI
- AWS Bedrock
- ELT
- Amazon SageMaker
- Azure ML
- Data Lakes
Возможные вопросы на собеседовании
Проверка опыта в пресейле и умения оценивать проекты.
Расскажите о случае, когда вам нужно было оценить объем работ и бюджет для сложного AI-проекта с высокой степенью неопределенности. Как вы минимизировали риски?
Оценка технической экспертизы в современных архитектурах данных.
Какие критерии вы используете при выборе между архитектурой Data Lakehouse на базе Databricks и облачным хранилищем Snowflake для крупного корпоративного клиента?
Проверка знаний в области MLOps и жизненного цикла моделей.
Как вы подходите к проектированию MLOps-фреймворка для обеспечения непрерывного обучения и деплоя моделей в продакшн?
Оценка коммуникативных навыков и работы со стейкхолдерами.
Как вы объясняете концепцию 'Agentic AI' или LLM-агентов нетехническому заказчику, чтобы обосновать инвестиции в эти технологии?
Проверка опыта работы в агентской/консалтинговой среде.
Опишите ситуацию, когда требования клиента в ходе реализации проекта начали противоречить первоначальной архитектуре. Как вы разрешили этот конфликт?
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