Forward Deployed Engineer – Databricks - Forensic Discovery & Financial Crime

Deloitte•Tampa, FL

132d•$134,500 - $265,100•Onsite

About The Position

Forward Deployed Engineers at Deloitte work alongside clients to help turn artificial intelligence opportunities into scalable business solutions. As a Senior Consultant - Forward Deployed Engineer (FDE), you will design, build, and implement AI-enabled applications and data solutions in enterprise environments. This role combines software engineering, data engineering, and client-facing delivery to help move solutions from concept to production. If you can translate technical complexity into business value, this role offers the opportunity to help clients accelerate adoption of generative AI capabilities.

Requirements

Bachelor’s degree, or equivalent experience, in Computer Science, Data Science, Engineering, or a related field
3+ years of experience in software engineering, data engineering, data science, analytics engineering, or technical delivery roles, with experience in Amazon Web Services (AWS), Microsoft Azure, Google Cloud, or comparable cloud platform services
1+ years of experience with Databricks, including hands-on experience with one or more of the following: DBRX, MLflow, Vector Search, or Databricks AI Gateway
1+ years of experience leading project workstreams or client engagements, including translating business requirements into technical solutions and aligning delivery priorities with stakeholders
1+ years of hands-on experience building and deploying artificial intelligence (AI), generative artificial intelligence (GenAI), or large language model (LLM)-powered solutions in client or production environments
Demonstrated proficiency building and shipping production code with AI-assisted development tools, including the judgment to direct, review, and correct AI-generated output and to maintain engineering guardrails such as code review, testing, type checking, and linting
Experience presenting, defending, and iterating on technical designs and architectures with client and internal stakeholders, and incorporating feedback through to delivery
Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
Limited immigration sponsorship may be available

Nice To Haves

Experience supporting anti-money laundering (AML), fraud, financial crime, investigations, or compliance technology use cases
Experience with Spark, Airflow, dbt, streaming, data modeling, feature engineering, experimentation, or model evaluation
Experience with machine learning operations (MLOps) or large language model operations (LLMOps), including evaluation frameworks, model monitoring, or prompt management
Experience integrating LLM-based solutions with enterprise systems through APIs, microservices, or event-driven architectures
Experience delivering software within enterprise security and compliance processes, such as security and architecture design reviews, data and privacy impact assessments, and identity and access management
Working knowledge of how modern large language models behave in applications, including tool and function calling, structured outputs, evaluation of model outputs, and the trade-offs between generative and deterministic approaches

Responsibilities

Collaborate with client stakeholders to define business needs, operational constraints, priority use cases, and measurable success criteria.
Design, build, and integrate AI-enabled applications, application programming interfaces (APIs), machine learning models, data pipelines, and microservices tailored to client environments.
Use AI-assisted development workflows to accelerate delivery while maintaining code quality, security, and maintainability.
Lead implementation activities required to move solutions into production, including architecture, security, privacy, and access reviews.
Troubleshoot technical and integration issues and optimize performance across Databricks and cloud-based enterprise environments.
Create reusable assets, document workflows and support processes, and help client teams build the capabilities needed to sustain and extend delivered solutions.