Full Job Description
You are:
As a Forward Deployed Technical Consultant-Databricks, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. You will design, build, and operationalize enterprise-grade data and agentic AI solutions in Databricks and Azure Data Services. Your role spans the full solution lifecycle - assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and DevOps & MLOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems. You will design and implement autonomous agents using Databricks Mosaic AI Agent Framework and frameworks like LangChain or AutoGen.
You'll work closely with analytics, data science, and cloud teams to ensure reliable, high-performance data delivery for the clients we serve.
THE WORK
• Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions
• Architect, develop, and maintain scalable, low-latency data pipelines to ingest and transform diverse datasets leveraging Azure Databricks workflows and Spark technologies.
• Design and optimize lakehouse architecture using Delta Lake tables following Bronze, Silver, and Gold layers to ensure efficient, reliable, and governed data storage.
• Design and implement autonomous agents using Databricks Mosaic AI Agent Framework and frameworks like LangChain or AutoGen
• Build and optimize vector search indexes using Databricks Vector Search for accurate context retrieval.
• Design AI agents with retrieval, orchestration, tool invocation, evaluation harnesses, and lifecycle observability.
• Process large-scale distributed datasets on the Databricks Intelligence Platform with Apache Spark.
• Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps & MLOps
• Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC
• Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites
• Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production
• Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools
• Justify the value of model approaches in business problems
• Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production
This is a hybrid role in Mississauga/Montreal and requires 3 days per week in the office/client location
BASIC (REQUIRED) QUALIFICATION
• Bachelor's degree or completion of a college program in a related discipline
• Minimum 3 years of experience working with Microsoft Azure cloud data services.
• Minimum 3 years of hands-on experience with Databricks : PySpark, Delta Lake, Auto Loader, Lakehouse Medallion Architecture (Bronze, Silver, Gold).
• Experience with Git-based version control and CI/CD pipelines (Azure DevOps or GitHub Actions).
• Minimum of 3 years of experience in applying theoretical foundations of computer science, including computer system architecture, and programming
• Minimum of 1 years of experience in distributed computing systems and architecture that may include big data, high-performance compute, scientific compute, grid and cloud computing, distributed networks
English is required for this position as this role will regularly interact with stakeholders across Canada, US and other countries across our Global footprint where English is the common language. Due to the significant high volume of interactions with these English-speaking stakeholders, which is inherent to this position, it is not possible to reorganize the company's activities to avoid this requirement.
#LI-NA-FY25 #LI-MP
PREFERRED QUALIFICATION
• Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks.
• Experience working with language models like LLM's APIs and optimizing their usage for specific applications.
• Experience in MLOps/LLMOps (CI/CD for ML and LLM Lifecycle)
• Genie product Family
• Databricks certified Data Engineer Professional (2025)
• Strong written & verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders
• Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams
Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location,
role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation, based on full-time
employment, for roles that may be hired as set forth below.
The recruiting efforts for this position are intended to fill a brand new position.
The base pay range shown below is intended as a guideline to reflect the majority of offers for this role.
It does not represent a maximum limit - in some cases, actual compensation may exceed the range where appropriate.
Information on benefits is here: https://www.accenture.com/ca-en/careers/local/benefits
Role Location Annual Salary Range British Columbia/Ontario/New Brunswick $75,400 to $125,400
