Role Description
POSITION OVERVIEW
We are seeking two senior Resident Solutions Architects / Forward Deployed Engineers to lead hands-on Databricks implementations for enterprise customers. The strongest candidates will bring deep Databricks ecosystem expertise, proven Databricks Apps development experience, and practical AI experience on the platform. This is a delivery-focused role for a trusted technical advisor who can design, build, deploy, and optimize production solutions.
Location: 100% remote
Visa: GC / USC ONLY !! (No GC EAD too)
KEY RESPONSIBILITIES
- Lead customer-facing Databricks engagements from discovery and architecture through production deployment and adoption.
- Design and develop Databricks Apps and production-grade data/AI solutions using Python or Scala, SQL, Apache Spark, Delta Lake, and Databricks platform services.
- Build reference architectures and scalable solutions across batch/streaming data engineering, analytics, AI/ML, and GenAI use cases.
- Own technical delivery: write and review code, troubleshoot complex issues, tune Spark workloads, and improve performance, reliability, and cost.
- Implement CI/CD, MLOps, security, governance, observability, and operational best practices for enterprise deployments.
- Partner with customer stakeholders, project managers, account teams, engineering, and support to manage scope, risks, dependencies, and escalations.
- Translate complex technical concepts into clear recommendations, phased roadmaps, and measurable customer outcomes.
REQUIRED QUALIFICATIONS
- 17+ years of overall IT experience, including senior architecture, engineering, consulting, or platform delivery responsibilities.
- 5+ years of recent, hands-on experience across the Databricks ecosystem; demonstrated delivery of multiple production implementations.
- Strong Databricks Apps development experience, including secure application architecture, data access, deployment, and lifecycle management.
- Deep expertise in Apache Spark and distributed computing, including runtime behavior, optimization, scalability, and production troubleshooting.
- Advanced coding skills in Python and/or Scala plus strong SQL and data architecture fundamentals.
- Deep expertise in at least one cloud platform (AWS, Azure, or GCP) and working knowledge of a second.
- Proven consulting and executive-facing communication skills, with the ability to build trust and guide technical decisions.
HIGHLY PREFERRED
- Hands-on AI/ML or GenAI experience on Databricks, including MLflow/Mosaic AI, model serving, vector search, RAG, agents, or production MLOps.
- Databricks Data Engineer Professional or comparable Databricks certification.
- Experience scoping professional services engagements, estimating effort, and defining technical deliverables.
Pay: $75.00 - $80.00 per hour
Expected hours: 40.0 per week
Work Location: Remote
About Forward Deployed Engineering
Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.
Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.
Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.
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