Databricks Associate Forward Deployed Engineer

About the Role

The Deloitte AI & Engineering team transforms technology platforms, drives innovation, and makes a significant impact on client success by reimagining and reengineering critical business operations and processes. As a Databricks Associate Forward Deployed Engineer (FDE), you will work closely with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This role requires a highly motivated practitioner who builds working software with speed and precision, confidently engages with senior stakeholders and engineers, and delivers measurable business impact from day one.

Key Responsibilities

Client Engagement

• Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
• Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
• Lead working sessions to shape solutions and drive client outcomes.
• Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
• Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

• Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
• Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
• Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
• Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
• Design extensible functionality, support sprint sizing, and align solutions with senior team members.
• Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.

Requirements & Tech Stack

Qualifications Required

• Bachelor's degree (or equivalent) in Computer Science, Data Science, Engineering, or related field.
• Active US government security clearance (minimum Secret level).
• 2+ years of experience in software engineering, data engineering, data science, or analytics engineering.
• 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments.
• 1+ years of experience with Databricks including hands-on experience with one of the following key platform technologies: Databricks features for data engineering, data science, and analytics including Lakeflow Connect, Agent Bricks, and Databricks Apps.
• 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions.
• 1+ years of experience building reliable, maintainable, and well-documented code and CI/CD DevOps in Databricks.
• Ability to travel 50%, on average.
• Must be legally authorized to work in the United States without the need for employer sponsorship.

Qualifications Preferred

• Databricks certifications (e.g., Data Engineer Professional, Machine Learning Professional) are highly preferred.
• Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking).
• Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments.
• Data engineering experience with Spark, Airflow/dbt, streaming, data modeling, or ML/data science background feature engineering, experimentation, or model evaluation.
• Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management.
• Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures.
• Experience operating within hybrid onshore/offshore teams.
• Familiarity with security, privacy, and compliance considerations in regulated enterprise environments.

Skills

• Ability to work independently and collaborate as part of a team.
• Effective written and verbal communication skills.
• Meticulous attention to detail and quality of work product.
• Ability to build and sustain professional relationships.
• Ability to lead projects or workstreams.
• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment.
• Strong interpersonal skills and professional demeanor.
• Ability to meet deadlines.
• Ability to mentor and provide clear guidance to others.