Forward Deployed Engineer - Databricks - Forensic Discovery & Financial Crime at Deloitte
Atlanta, GA
$134,500–$265,100from the description
Jul 1, 2026
Atlanta, GA
Jul 21, 2026
What this job asks for AI summary
A client-facing engineering role embedded within Deloitte's Forensic, Discovery, & Financial Crime practice, focused on building and deploying AI and data solutions on Databricks and cloud platforms. Day-to-day work spans designing data pipelines, APIs, and LLM-powered applications, moving them from prototype to production within enterprise security and compliance constraints. Best suited to engineers comfortable bridging technical delivery and direct client engagement.
Mid level · 3+ years · National · Full-time
Advertised as Senior, but the requirements read as Mid.
“or” means any one of them counts — you don't need all of them.
Posted 4 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Rare in this occupation — lead with these, and say what you built with them.
What the occupation pays Median $138,970 (middle half $107,524–$175,762). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (8)
No specific work location is stated in the posting; the role requires 50% travel on average, suggesting client-site delivery across multiple locations. No CBSA has been assigned.
The title 'Senior Consultant' maps to Deloitte's internal career ladder, not the standard engineering seniority ladder. The actual requirements (3+ years total, 1+ year with Databricks/LLMs) are consistent with a Mid-level engineer; the role is classified Mid accordingly.
The degree requirement accepts 'equivalent experience' in lieu of a Bachelor's, so no formal degree is hard-gated.
The cloud platform requirement names AWS, Azure, and GCP as interchangeable options; AWS is listed first and used as the primary skill name with the others as alternatives.
The Databricks hands-on requirement lists DBRX, MLflow, Vector Search, and Databricks AI Gateway as 'one or more of the following' — these are interchangeable satisfiers of the same gate. MLflow is used as the primary name with the others as alternatives.
LLMs and GenAI are listed as a combined required gate ('AI, GenAI, or LLM-powered solutions'); both are emitted as separate required skills given their distinct meanings in practice.
Spark, Airflow, dbt, MLOps/LLMOps, and API/microservices integration experience all appear under the 'Preferred' section.
The AML/fraud/financial crime domain experience is listed as preferred but is not emitted as a skill — it names no specific technology or tool.
Read the full posting
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