Lead Forward Deployed Engineering, Data Science & Integration

Salesforce

Confirmed live 2 days ago High trust
Remote

Quick summary

Work type
Remote
Location
Herndon, VA
Salary
$172,500–$260,100 / yr
Posted
8 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $204k
This role $216k
$160k most similar roles pay here $271k

This role pays more than 65% of similar roles. Most pay $176,950–$230,450 — the shaded band above. At the midpoint, this role pays about $216k versus about $204k for comparable roles.

Based on 240 similar postings.

Employer

About Salesforce

Salesforce is the world''s leading customer relationship management (CRM) platform, offering cloud-based software for sales, service, marketing, analytics, and application development. Industry: Enterprise Software & Cloud Computing

Salesforce currently has 106 open roles on FindRole.

Listed pay typically runs $148,500–$260,100 across 98 roles with salary data.

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At a glance

TL;DR · Lead Forward Deployed Engineering, Data Science & Integration

Lead Forward Deployed Engineering - Data Science & Integration is a senior-level role within the Public Sector team, where you will serve as a technical lead embedded directly with customers. You will act as a bridge between mission owners and internal engineering teams to design, build, and deploy bespoke data science pipelines, intelligent automation, and enterprise integration solutions in national security environments. Your daily work involves developing advanced AI/ML systems, managing the full data lifecycle from modeling to ETL construction, and orchestrating complex workflows. You will utilize technologies including Python, Java, SQL, MuleSoft, Regrello, and various cloud platforms like Snowflake or Databricks. The role focuses on solving critical integration challenges for the Department of Defense and Intelligence Community by delivering scalable production models and automated processes in highly regulated, secure environments to improve mission-readiness and operational efficiency.

What you'll do

  • Design and deploy end-to-end data science pipelines, including predictive models and LLM-augmented workflows, for defense and intelligence clients.
  • Architect and implement enterprise integration solutions using platforms like MuleSoft to connect disparate data sources in secure environments.
  • Build and orchestrate automated operational workflows using tools such as Regrello to optimize logistics and supply chain processes.
  • Manage the full data lifecycle on-site with customers, including data modeling, ETL/ELT construction, and feature engineering.
  • Develop rapid prototypes and MVPs alongside customer teams to demonstrate technical capabilities and accelerate mission-aligned delivery.
  • Serve as a forward-deployed technical lead to translate complex mission requirements into actionable integration roadmaps for senior stakeholders.
  • Collaborate with internal engineering teams to co-develop new integration patterns based on feedback from frontline customers.
  • Mentor junior engineers and develop reusable playbooks, templates, and assets for the broader engineering community.

What we're looking for

  • Must be a U.S. citizen (born or naturalized) living on U.S. soil who does not hold dual citizenship.
  • Must be eligible for and willing to obtain a U.S. Security Clearance and pass a Minimum Background Investigation.
  • Requires 8+ years of experience in hands-on, end-to-end delivery of scalable production solutions.
  • Requires a strong background in Computer Science, Data Science, or a related engineering discipline.
  • Must have expert-level proficiency in programming languages such as Python, Java, and SQL.
  • Requires extensive experience building AI/ML solutions, including MLOps pipelines, LLM integration, and agentic frameworks.
  • Requires expertise in enterprise integration platforms (e.g., MuleSoft) and workflow orchestration tools (e.g., Regrello).
  • Must be able to travel 50-75% of the time to customer sites, including classified facilities.

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