AI Engineer - Forward Deployed Engineer Associate Manager · Databricks · Reinvention Centers

Accenture•Columbus, OH

24d•$62,800 - $261,500•Hybrid

About The Position

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. The ATCs make a tremendous impact in solving our clients’ business problems by leveraging innovation, intelligence, industry insights, new IT, and new technology skills. 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 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.

Requirements

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)

Nice To Haves

An AI Native Engineer with strong experience building GenAI solutions and deep expertise in productionizing AI applications on the Databricks Intelligence Platform.
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.

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.