AI Engineer - Forward Deployed Engineer · Databricks · Reinvention Centers

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 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.

• Minimum 4 years of engineering experience on Databricks and large‑scale big data projects (Delta Lake, DLT, Apache Spark, Unity Catalog). 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).

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.

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.

We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.

Accenture is an EEO and affirmative Action Employer of Veterans/Individuals with Disabilities. Accenture is committed to providing veteran employment opportunities to our service men and women.

Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.

Candidates who are currently employed by a client of Accenture or an affiliated Accenture business may not be eligible for consideration.

Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process. Further, at Accenture a criminal conviction history is not an absolute bar to employment.

The Company will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or…