EH-FY27-Consulting-S&T-Strategy-Senior Consultant-TS-SFL-AI Strategy

Summary Position Summary AI Strategic Architect SFL Scientific, a Deloitte Business practice brings together several key capabilities to architect integrated programs that transform our clients’ businesses, including Strategic Growth Transformation, Transformation Strategy & Design, Technology Strategy & Business Transformation, and AI & Data Strategy.

Professionals will serve as trusted advisors to our clients, working with them to make clear data-driven choices, using the latest state-of-the-art technologies, to advise our clients on how to leverage AI technologies and working directly with them to design and implement novel solutions that drive value.

We are hiring AI Strategic Architects to support and lead development, deployment, and maintenance of novel AI solutions and cloud architectures across healthcare, manufacturing, energy, retail, finance, and other sectors.

Work you’ll do As an AI Strategic Architect at SFL Scientific, a Deloitte Business, you’ll work with a cross-functional strategy and AI team to bring solutions to life.

We seek individuals with a strategic mindset for planning and implementing AI systems for large-scale organizations on both on-prem and cloud infrastructure.

You will be responsible for designing, deploying, benchmarking, and scaling solutions from test environments to global production, impacting millions. Key tasks also include gathering and understanding business requirements, identification of performance gaps, and the design and implementation of scalable solutions in the client’s environment.

Successful candidates will work with non-technical stakeholders, IT teams, and existing solution teams to translate requirements into a technical design, handling both strategic design and implementation tasks, to drive value for our clients.

Design & Planning :

• Work directly with clients, stakeholders and user groups to understand requirements and communicate technical decisions and trade-offs.
• Interact with client IT teams to ensure solutions are compatible with their requirements and that deployment schedules are timely, efficient and well-coordinated between teams.
• Integrate with a broader delivery team to design technical specifications that outline the resources, functions, interfaces and architecture of a scaled solution applicable to the common hyperscalers (AWS, GSP, Azure).
• Assess small scale functional AI solutions and determine performance gaps, required enhancements and technical solutions for deploying those solutions at scale - this spans data security, latency considerations, large concurrent workloads, performance expectations, user requirements.
• Assist in documentation required for successful product deployment, this could include sustain processes, user guides, interface schematics etc.

Execution :

• Sprint planning and implementation of technical architectures, this would include implementing CICD pipelines, deploying cloud resources, implementing Kubernetes based deployments, networking across cloud resources, ETL pipelines.
• Design and development of web-based UI’s.
• Implementation and testing of core application enhancements with a focus on AI workloads (ex. RAG applications, multi-agent workloads, AI modeling enhancements).

The Team SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.

Qualifications:

• Bachelor’s degree in a relevant STEM Field (ex. Data Science, Computer Science, Engineering, Mathematics, Physics)
• 5+ years of experience working in data science, data engineering, software engineering, and/or MLOps.
• Experience with cloud deployment (AWS, Azure, GCP), such as designing, building, and scaling using cloud tools such as AWS SageMaker or Azure ML Studio.
• 5+ years working with core cloud application development tools & s…