Qualifications
Responsibilities
Benefits
You Are
A Senior AI Native Engineer who builds, leads, and scales world-class AI/ML professional services on the Databricks Intelligence Platform. You develop executive relationships with VP+, CIO, and CDO stakeholders as a trusted advisor on complex AI transformations, align with Field Engineering and Sales Leaders on strategic accounts, and shape cross-functional influence across Product, R&D, and GTM. You lead AI PS initiatives, design reusable engagement models for global repeatability, own OKRs for AI-services led accounts, and represent Databricks as a thought leader in AI/ML.
The Work
You will embed directly with clients as both technologist and trusted advisor. You will partner with stakeholders to define use cases, rapidly prototype, 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. • Architect AI-native solutions on Databricks (Mosaic AI, Vector Search, Model Serving, MLflow) with Unity Catalog governance, scaling reusable patterns across customer engagements.
Establish Lakehouse data foundations (Delta Lake, DLT, Unity Catalog) that power production AI across customer portfolios.
Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration.
Leverage containerization, microservices, serverless, and event-driven architectures to deliver scalable AI-native systems.
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 effectiveness.
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 4 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:
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 10/02/2026.
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:
Role Location Annual Salary Range
California $94,400 to $293,800
Colorado $94,400 to $253,800
Connecticut $94,400 to $253,800
District of Columbia $100,500 to $270,300
Illinois $87,400 to $253,800
Maine $80,400 to $216,200
Maryland $94,400 to $253,800
Massachusetts $94,400 to $270,300
Minnesota $94,400 to $253,800
New York $87,400 to $293,800
New Jersey $100,500 to $293,800
Ohio $87,400 to $235,000
Virginia $87,400 to $270,300
Washington $100,500 to $270,300
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