We are:
The Advanced Technology Centers (ATCs) are the engine for reinvention in our clients' transformation journey. Powered by more than 255,000 people across 24 countries, ATCs provide our clients with seamless access to industry insights and innovative technology solutions.
Stronger together
The Advanced Technology Centers (ATCs) make a tremendous impact in solving our clients' business problems by leveraging innovation, intelligence, industry insights, new IT, and new technology skills. With the global environment changing at a faster pace, our clients are facing unprecedented challenges, and they need us more than ever before. As a Network, ATCs are positioned to unlock greater opportunities and exponential value for our clients.
The value for our clients and our people:
For our clients, the Network provides the strength of our geographic diversity, greater resilience, and seamless access to the deepest industry knowledge, the latest in Gen AI solutions, and tech expertise from around the world. For our people, it brings an opportunity to shape truly boundaryless career paths in a highly collaborative team of experts where they can learn from each other and solve the world's most complex client challenges.
You Are:
An AI Native Engineer with strong experience building GenAI solutions and deep expertise in productionizing AI applications on the Databricks Intelligence Platform. You thrive in customer-facing complexity and deliver outcomes by applying the latest techniques from Mosaic AI Research, designing RAG and multi-agent systems with HuggingFace, LangChain, and DSPy, and shipping production-grade GenAI at scale on AWS, Azure, or GCP.
The Work:
You will embed directly with clients as both technologist and trusted advisor. You will partner with stakeholders to define use cases, rapidly proto@type, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains.
Responsibilities:
Design and engineer enterprise-ready AI agents encompassing retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
Build RAG and multi-agent systems on Databricks using Mosaic AI, Vector Search, Model Serving, and MLflow; govern data and models through Unity Catalog.
Develop data and feature foundations on the Lakehouse (Delta Lake, DLT, Unity Catalog) that feed production AI applications.
Tailor and deploy agentic applications across industries such as finance, healthcare, and retail.
Conduct design workshops, proofs of concept, and code-with sessions with client stakeholders. - Define and use metrics to measure agent accuracy, latency, safety, and cost efectiveness.
Process large-scale distributed datasets on the Databricks Intelligence Platform with Apache Spark.
Integrate LLM solutions with APIs, model monitoring, and prompt management.
Operate MLOps / LLMOps pipelines with CI/CD across the ML and LLM lifecycle.
This is a hybrid role in Dallas, TX and requires 3 days per week in the office. May consider qualified applicants in Columbus, OH; Tampa, FL; Atlanta, GA; Houston, TX.
Travel may be required for this role. The amount of travel will vary from 25% to 75% depending on business need and client requirements.
Here's What You Need:
Minimum 4 years of engineering experience on Databricks and large-scale big data projects (Delta Lake, DLT, Apache Spark, Unity Catalog). You've also built API layers that expose data and AI/ML capabilities to enterprise systems.
Minimum 5 years of experience in Python, Java, or equivalent. Comfortable with evaluation tooling, logging, monitoring, and observability.
Minimum 1 year experience in designing and shipping agentic AI solutions in production.
Minimum 1 year experience in shipping agentic solutions in production (agents, orchestration, @context engineering, RAG, workflows) using AI platforms (OpenAI, Claude, Vertex AI, open source) and Databricks AI tooling (Mosaic AI, Vector Search, Model Serving, MLflow).
Minimum 2 years experience in shipping to production: CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging. Practical MLOps and LLMOps experience across the ML and LLM lifecycle (model training, serving, monitoring, prompt management).
Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate Degree, must have minimum 6 years work experience)
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 for roles that may be hired as set forth below. We anticipate this job posting will be posted until 06/30/2026. Accenture offers a market competitive suite of benefits including medical, dental, vision, life, and long-term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off. See more information on our benefits here:
U.S. Employee Benefits | Accenture (https://www.accenture.com/us-en/careers/local/benefits)
Role Location Annual Salary Range California $73,800 to $261,500 Cleveland $68,300 to $209,200 Colorado $73,800 to $225,900 District of Columbia $78,500 to $240,600 Illinois $68,300 to $225,900 Maryland $73,800 to $225,900 Massachusetts $73,800 to $240,600 Minnesota $73,800 to $225,900 New York $68,300 to $261,500 New Jersey $78,500 to $261,500 Washington $80,200 to $240,600
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