Senior AI Engineer / Solutions Architect – SFL Scientific
Data and Analytics | AI and Data Architecture and Solution Design
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Position Summary
Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey—before, during, and after any major transformational projects or transactions.
Are you eager to shape the future of emerging technologies? Imagine joining an acclaimed team where career paths span from account executives and data scientists to AI strategists, machine learning specialists, and data engineers. SFL Scientific, a Deloitte Business, is looking to add a Senior AI Engineer to their vibrant environment. SFL Scientific is part of our broader Strategy Offering within the Strategy & Transactions practice, whose specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Take the next step in your technical journey—develop your leadership, consulting acumen, and reputation as a trailblazer within the AI engineering field by joining our team!
Recruiting for this role ends on 5/31/2026.
Work You’ll Do
As a Senior AI Engineer/Solutions Architect, you’ll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and deployment services for our novel machine learning applications. Key to this role is the ability to demonstrate both traditional data engineering expertise, leveraging cloud/enterprise/open-source solutions, and constructing IT infrastructure for organizations across a wide variety of industries.
In our consultative approach, we are platform agnostic and committed to providing the best technical solutions for each client and solution. Our engineering team leverages emerging technologies and best practices across data security, documentation, cloud services and engineering architecture to create solutions and products that address complex issues and business problems faced by global organizations. Some of our novel use cases include cancer detection, drug discovery, optimizing population health and clinical trials, autonomous systems and edge AI, and renewable energy. Key responsibilities:
- Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
- Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
- Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
- Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
- Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
- Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
- Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
- Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
- Mentor, motivate, and coach junior members on technical best practices and inspire professional development
The Team
Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
Specifically, 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
Required:
- Bachelor’s degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience
- 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
- 4+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
- 4+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
- 2+ years of experience managing teams in technical delivery and delivering complex and critical projects
- 2+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins
- 2+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
- 2+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
- Live within commuting distance to one of Deloitte’s consulting offices
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
- Limited immigration sponsorship may be available
Preferred:
- Master's degree in Computer Science, Engineering, Physics, etc. or related STEM field
- AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect)
- 2+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $107,600 to $198,400.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
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Requisition code: 319216
Job ID 319216