Databricks Forward Deployed Engineer - GPS

Experteer Overview As a Databricks Forward Deployed Engineer (FDE), you rapidly prototype and deliver GenAI-enabled solutions for clients, working with senior teams to translate business needs into tangible outcomes. You build production-ready AI tooling and guide stakeholders from design to delivery, contributing to reusable assets and best practices. This role sits at the intersection of engineering, AI, and client advisory to drive measurable impact from day one. You will collaborate across cross-functional teams in a government and public services context, shaping innovative data and AI solutions at scale. Compensation / Benefits * Embed with clients to identify business needs and translate GenAI use cases into solutions * Partner with product owners, architects, and engineers to align delivery priorities * Lead sessions to shape solutions and drive client outcomes * Prototype and deliver working AI solutions using domain expertise and cutting-edge capabilities * Mentor junior team members within an FDE pod * Build AI-enabled solutions and workflows across enterprise AI platforms * Develop scalable engineering patterns, tool-use approaches, and human-in-the-loop controls * Apply architecture decisions balancing quality, safety, latency, cost, and risk * Deliver production-quality code with strong CI/CD, testing, logging, versioning, and documentation * Design extensible functionality and align with sprint planning and senior teammates * Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations Tasks * 4+ years of experience in software engineering, data engineering, data science, or analytics engineering * 2+ years building and deploying GenAI/LLM-powered solutions in client or production environments * 2+ years of Databricks experience including Lakeflow Connect, Agent Bricks, and Databricks Apps * 2+ years leading project workstreams and translating business problems into AI solutions * 2+ years of reliable, maintainable code and CI/CD DevOps in Databricks * Active US government security clearance (minimum Secret level) * Bachelor’s degree (or equivalent) in Computer Science, Data Science, Engineering, or related field * Ability to travel 50% on average * Must be legally authorized to work in the United States without sponsorship now or in the future * Preferred: Databricks certifications (Data Engineer Pro, Machine Learning Pro) are highly preferred * Experience with cloud environments (AWS, Azure, and/or Google Cloud) and related platform services * Experience with MLOps/LLMOps practices and API-driven enterprise integrations * Security, privacy, and compliance considerations in regulated environments Key requirements *

at members within an FDE pod * Build AI-enabled solutions and workflows across enterprise AI platforms * Develop scalable engineering patterns, tool-use approaches, and human-in-the-loop controls * Apply architecture decisions balancing quality, safety, latency, cost, and risk * Deliver production-quality code with strong CI/CD, testing, logging, versioning, and documentation * Design extensible functionality and align with sprint planning and senior teammates * Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations Tasks * 4+ years of experience in software engineering, data engineering, data science, or analytics engineering * 2+ years building and deploying GenAI/LLM-powered solutions in client or production environments * 2+ years of Databricks experience including Lakeflow Connect, Agent Bricks, and Databricks Apps * 2+ years leading project workstreams and translating business problems into AI solutions * 2+ years of reliable, aaaaaaaaaa to code and CI/CD DevOps in Databricks * Active US government security clearance (minimum Secret level) * Bachelor’s degree (or equivalent) in Computer Science, Data Science, Engineering, or related field * Ability to travel 50% on average * Must be legally authorized to work in the United States without sponsorship now or in the future * Preferred: Databricks certifications (Data Engineer Pro, Machine Learning Pro) are highly preferred * Experience with cloud environments (AWS, Azure, and/or Google Cloud) and related platform services * Experience with MLOps/LLMOps practices and API-driven enterprise integrations * Security, privacy, and compliance considerations in regulated environments Key requirements *