> Markdown version of [/jobs/ext/2016062-lead-databricks-forward-deployed-engineer-gps](https://www.wearedevelopers.com/jobs/ext/2016062-lead-databricks-forward-deployed-engineer-gps). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Lead Databricks Forward Deployed Engineer - GPS

- **Company:** Deloitte T.T.L.
- **Location:** Arlington, VA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Continuous Integration, Global Positioning Systems (GPS), Systems Development Life Cycle, Software Deployment, Large Language Models, Information Technology, Machine Learning Operations, Databricks
- **Published:** August 10, 2026
- **Apply:** https://us.experteer.com/career/view-jobs/lead-databricks-forward-deployed-engineer-gps-rosslyn-va-usa-58886891

## About the Role

_ engineers and enforce consistency in SDLC, CI/CD, and documentation * Coordinate multi-pod engagements to ensure reliable architecture and consistent client experience * Contribute to pipeline development and deal shaping during client pursuits and platform partner engagements Tasks * Bachelor in Computer Science, Data Science or Engineering (or equivalent) * Minimum Secret security clearance * 10+ years in software/data/analytics engineering * 6+ years building and deploying GenAI/LLM-powered solutions in production * 6+ years in Databricks with Lakeflow Connect, Lakebase, Agent Bricks, Model Serving, Genie, or Databricks Apps * 6+ years leading project workstreams and translating business problems into AI solutions * 5+ years building maintainable code with CI/CD in Databricks * Willingness to travel ~50% * Authorized to work in the United States without sponsorship * Professional Databricks certifications (required) Key requirements *

## Description

Experteer Overview In this role you lead embedded, forward-deployed engineering pods delivering GenAI solutions to Deloitte's most strategic clients. You set technical direction, maintain hands-on credibility, and drive production deployments across onshore and hybrid teams. You'll influence senior client stakeholders and ensure scalable, high-quality outcomes from prototype to production. This is a hands-on leadership role that combines architecture, delivery governance, and cross-functional collaboration to transform client platforms. Compensation / Benefits * Serve as the senior client-facing engineering partner for product, data, and platform initiatives * Lead onshore/offshore pods (2-5 engineers), manage delivery health, risk, and resource allocation * Architect and oversee GenAI solution delivery (LLM apps, copilots, knowledge search) and end-to-end RAG pipelines * Define evaluation metrics, governance, and quality bars; translate trade-offs for executive clients * Mentor junior engineers and enforce consistency in SDLC, CI/CD, and documentation * Coordinate multi-pod engagements to ensure reliable architecture and consistent client experience * Contribute to pipeline development and deal shaping during client pursuits and platform partner engagements Tasks * Bachelor in Computer Science, Data Science or Engineering (or equivalent) * Minimum Secret security clearance * 10+ years in software/data/analytics engineering * 6+ years building and deploying GenAI/LLM-powered solutions in production * 6+ years in Databricks with Lakeflow Connect, Lakebase, Agent Bricks, Model Serving, Genie, or Databricks Apps * 6+ years leading project workstreams and translating business problems into AI solutions * 5+ years building maintainable code with CI/CD in Databricks * Willingness to travel ~50% * Authorized to work in the United States without sponsorship * Professional Databricks certifications (required) Key requirements *


## Related Videos

- [Remote Driving on Plant Grounds with State-of-the-Art Cloud Technologies](https://www.wearedevelopers.com/videos/251-remote-driving-on-plant-grounds-with-state-of-the-art-cloud-technologies)
- [Creating Industry ready solutions with LLM Models](https://www.wearedevelopers.com/videos/899-creating-industry-ready-solutions-with-llm-models)
- [100 times more frequent deployments: How did we create a high performance team?](https://www.wearedevelopers.com/videos/1069-100-times-more-frequent-deployments-how-did-we-create-a-high-performance-team)
- [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source)
- [Lies, Damned Lies and Large Language Models](https://www.wearedevelopers.com/videos/1231-lies-damned-lies-and-large-language-models)
- [From Space to Software: Reliability Lessons 40 Years After Challenger](https://www.wearedevelopers.com/videos/100283-from-space-to-software-reliability-lessons-40-years-after-challenger)

## Related Articles

- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)
- [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)
- [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)
- [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix)
- [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)