The AI Data Engineer - Manager leads Deloitte's data architecture and engineering delivery to enable AI, ML, and GenAI initiatives. This onsite role in Portland, OR ensures data is trusted, secure, observable, and scalable, while coordinating onshore and offshore teams to translate use cases into production pipelines with governance and monitoring. Salary ranges from USD 130,800 to 241,000 per year.
Responsibilities
- Lead the data architecture and engineering delivery enabling AI, ML, and GenAI solutions with data that is trusted, secure, observable, and scalable from ingestion to consumption.
- Design and operationalize modern data and retrieval foundations to support LLM powered applications, including patterns such as RAG, embeddings, vector search, and governed access to structured and unstructured data.
- Manage day to day delivery with an onshore/offshore team, partnering with data science, ML engineering, and product stakeholders to translate use cases into production ready pipelines and platforms with strong data governance, lineage, quality controls, and monitoring.
- Blend hands on technical leadership with delivery management and team development, driving consistent engineering standards and measurable outcomes in client environments.
- Help define the AI/ML/GenAI technical direction and vision, ensuring alignment with strategic goals and digital transformation efforts.
- Translate the vision of business leaders into realistic technical implementations, while identifying misaligned initiatives and impractical use cases.
- Design end to end AI architectures, from data ingestion to model deployment, integrating with cloud and on premises systems.
- Select appropriate technologies from a pool of open source and commercial offerings, considering deployment models and integration with existing tools.
- Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage machine learning models and large language models.
- Conduct research to provide technical solutions to scale AI/ML powered features for real world challenges, making trade offs based on quality, scalability, performance, and cost.
- Lead the development of AI models such as machine learning, natural language processing, and computer vision, and implement scalable AI solutions.
- Collaborate with Enterprise, Application, Data & DevOps teams, Data scientists, ML & GenAI Engineers, and Business teams to pilot use cases and discuss best design.
- Gather inputs from multiple stakeholders to align technical implementation with existing and future requirements.
- Serve as a technical advisor to leadership, providing insights on AI trends, potential business impacts, and implementation best practices.
- Be responsible for the successful execution of AI powered applications using agile methodology.
- Audit AI tools and practices across data, models and software engineering, focusing on continuous improvement and feedback mechanisms.
- Contribute to standardizing CI/CD pipelines, user and service roles, and container creation, model consumption, testing, and deployment methodology based on business and security requirements.
- Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
- Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
- Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
- Break down client problems and bring an understanding of leading technology, analytics methods, tools, and operating model approaches.
- Build tools and capabilities that assist with data ingestion, feature engineering, data management, and organization.
- Design, implement, and maintain distributed computing solutions for data processing and model training, ensuring the security, scalability, and reliability of machine learning infrastructure.
- The Team section highlights the Insights, Innovation & Operate Offering, which enhances client operations through cutting edge technology, data, and a blend of technical and human expertise to deliver industry-specific solutions.
Requirements
- Bachelor's degree in Computer Science, Statistics, Data Science, Information Systems or related field.
- 6+ years of consulting experience leading delivery teams, including onshore and offshore team members.
- 6+ years of experience gathering non functional requirements and defining application architecture frameworks, including validation and testing deliverables.
- 5+ years of experience working in an AI environment.
- 5+ years of experience translating requirements into client ready design documents.
- 5+ years of experience in software application architecture analysis, design, and delivery.
- 5+ years of experience executing full system development life cycle implementations.
- Ability to travel 0-25 percent, on average, based on the work you do and the clients and industries/sectors you serve.
- Limited immigration sponsorship may be available.
Technologies
- Claude
- GPT/Codex
- Gemini
- AWS
- Google Cloud
- Azure
Benefits
- Discretionary annual incentive program
The Team
Our Insights, Innovation & Operate Offering is designed to enhance key aspects of our clients' businesses by leveraging cutting edge technology, data, and a blend of deep technical and human expertise. We innovate and deliver creative, industry specific solutions that streamline operations and accelerate speed to value.
Possible Locations
Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Costa Mesa, Dallas, Denver, Detroit, Hartford, Houston, Indianapolis, Jacksonville, Kansas City, Las Vegas, Los Angeles, McLean, Miami, Minneapolis, Morristown, Nashville, New Orleans, New York, Philadelphia, Pittsburgh, Portland, Raleigh, Richmond, Sacramento, San Antonio, San Diego, San Francisco, San Jose, Seattle, St. Louis, Stamford, Tampa, Tempe
