PowerToFly
Recent searches
  • Events
  • Companies
  • Resources
  • Log in
    Don’t have an account? Sign up
Filters
Clear All
Advanced filters
Job type
  • Reset Show results
Date posted
  • Reset Show results
Experience level
  • Reset Show results
Company
  • Reset Show results
Skills
  • Reset Show results
Clear All
Cancel Show Results
Active filters:
Results 13769 Jobs
Loading...
Loading more jobs...

No more jobs to load

No more jobs to load

AI Data Engineer, Manager - Tax Transformation
Save Job
Deloitte LLP

AI Data Engineer, Manager - Tax Transformation

Onsite Canada
Posted 2 hours ago
Save Job

Watch this video to learn more about Deloitte LLP

Job Details

If you are a technology leader energized by transforming global tax through digital solutions, join the US Tax Transformation technology team. In this role, you will help drive Deloitte's shift from "doing digital" to "being digital" by reimagining how we build and scale GenAI-enabled data products that power client delivery and internal operations. You will lead engineering efforts across enterprise-grade platforms, working with cross-functional teams to design, build, and run high-performing data and AI solutions that create measurable value.

Recruiting for this role ends on May 31, 2026.

Work you'll do
As an AI Data Engineer, Manager on the Tax Transformation technology team, you will be responsible for leading GenAI and data engineering initiatives that enable digital transformation across enterprise products. You will:
  • Lead the design, build, deployment, and operations of analytics platforms that process terabytes of data at scale.
  • Design and implement data ingestion, real-time streaming, batch processing, and extract-transform-load (ETL) pipelines across multiple storage technologies.
  • Tune complex Structured Query Language (SQL) queries and data flows for performance and reliability.
  • Design and operationalize multi-agent Generative AI workflows (planner/worker patterns, tool use, memory, retries/fallbacks) integrated with enterprise data and retrieval services.
  • Build and maintain agent tool backends, including search/retrieval, document ingestion, SQL generation guardrails, and governance checks, with strong observability and quality evaluation.
  • Own the vector retrieval layer, including embedding pipelines, indexing strategies, hybrid search patterns, and latency/throughput optimization for Retrieval-Augmented Generation (RAG).
  • Lead implementation of Zilliz Cloud/Milvus in production, including collection design, partitions, index selection/tuning, bulk ingest patterns, and retrieval performance tuning.
  • Implement MongoDB-based data services for GenAI workloads, including schema design, aggregation pipelines, change streams, and sharding/scale patterns.

The team
Deloitte Tax LLP's Tax Transformation Office (TTO) is responsible for the design, development, and deployment of innovative, enterprise technology, tools, and standard processes to support the delivery of tax services. The TTO team focuses on enhancing Deloitte Tax LLP's ability to deliver comprehensive, value-added, and efficient tax services to our clients. It is a dynamic team with professionals of varying backgrounds from tax technical, technology development, change management, Six Sigma, and project management. The team consults and executes on a wide range of initiatives involving process and tool development and implementation including training development, engagement management, tool design, and implementation.

Qualifications

Required:
  • Ability to perform job responsibilities within a hybrid work model that requires US Tax professionals to co-locate in person 2 - 3 days per week.
  • Bachelor's degree in computer science, engineering, or a relevant discipline.
  • 5+ years designing, building, and operating production-grade data platforms and pipelines using Python and Structured Query Language (SQL), distributed processing (Apache Spark), streaming (Apache Kafka), cloud data services (Microsoft Azure), and data storage across SQL and NoSQL systems.
  • Proven track record of delivering Retrieval-Augmented Generation (RAG) to production, including embedding generation, vector indexing, hybrid retrieval, and latency/throughput optimization evidenced by shipped features, runbooks, and performance metrics.
  • Demonstrated experience delivering vector databases such as Milvus or Zilliz Cloud to production, including collection design, index tuning, and metadata filtering evidenced by deployed clusters, index configurations, and observed retrieval performance.
  • Hands on experience in the design and operation of MongoDB-based data services, including schema design, aggregation pipelines, indexing strategies, security configuration, and performance tuning.
  • Ability to travel 20%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.
  • One of the following active accreditations obtained:
    • Licensed CPA in state of practice/primary office if eligible to sit for the CPA
    • If not CPA eligible:
      • Licensed Attorney
      • Enrolled Agent
      • Technology Certifications:
        • AWS Certified Solutions Architect
        • Open Group Certified Architect (Open CA)
        • IASA's Certified IT Architect (Level F or A)
        • Certified SAFe DevOps Practioner
        • ITIL Certification
        • Certified Information Systems Security Professional (CISSP)
        • Project Management Professional (PMP)
        • Microsoft Azure

Preferred:
  • Experience leading cross-functional engineering teams delivering GenAI-enabled data products.
  • Leadership: Experience leading cross-functional engineering teams delivering GenAI-enabled data products.
  • GenAI orchestration & safety: 2+ years building multi-agent systems (agent graphs, tool-calling, structured outputs) with evaluation, safety guardrails, and observability (tracing, eval pipelines, quality metrics).
  • ML/DS enablement & MLOps: Experience supporting data scientists at scale, including model monitoring, feature stores (e.g., Feast/Vertex AI Feature Store), and data/model version management.
  • Data/ML pipelines & CI/CD: Hands-on with LLM data pipelines (preprocessing), CI/CD for ML/data pipelines (e.g., Kubeflow, MLflow, Airflow, SageMaker Pipelines), and real-time inference streaming (Kafka/Spark Structured Streaming).
  • Data platform & analytics: Strong data warehousing design/optimization, advanced SQL/performance tuning for high-volume flows, data quality automation/visualization, plus Power BI; cloud certification (Azure/AWS or similar) preferred.

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 $119,490 to $272,090.

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
Company Details
Deloitte LLP
 New York City, NY, United States
Work at Deloitte LLP

Don't imagine what's next. Discover it. We provide industry-leading audit & assurance services, consulting, tax and advisory services to many of... Read more

Did you submit an application for the AI Data Engineer, Manager - Tax Transformation on the Deloitte LLP website?