Onsite AI Data Engineer for Enterprise Deployments

Flipside; Boston (MA); On-site; USD 120,000 - 180,000; Full time

Job summary

edisyl is seeking a technically seasoned professional to embed inside client environments and make our AI agents work against data never prepared for them. You will solve a specific problem for each organization, using data such as CRMs, warehouses, and document archives.

You will partner with CTOs and Enterprise Data Strategists on each account, delivering measurable outcomes like leads written to CRM and pipelines running in production.

Qualifications

• 4–8 years combining hands-on data engineering with direct deployment or customer exposure — forward-deployed engineering, solutions engineering, data consulting, or technical implementation at a data or AI company.
• You've worked inside enterprise data environments and know what CRMs, warehouses, and legacy pipelines actually look like from the inside.
• SQL fluency — you think in queries, use DuckDB, dbt, or similar without looking things up; proficiency in Python preferred; comfortable reading and writing API integrations.
• Hands‑on experience building or deploying AI agent workflows; you know where LLMs break against real data problems.

Responsibilities

• Lead technical onboarding and implementation from data environment discovery through production deployment
• Build, configure, and troubleshoot data connectors, pipelines, and AI agent workflows inside client environments
• Work directly with Forge, Lattice, and Stratum — our agent framework, orchestration layer, and semantic intelligence system
• Serve as the primary technical point of contact for your accounts post-deployment
• Surface what you're learning in the field — product gaps, failure modes, recurring patterns — back to engineering
• Develop implementation playbooks from each engagement so the next one goes faster
• Partner with the Enterprise Data Strategist and CEO on pre-sale scoping, technical discovery, and proof-of-concept builds

Job description

edisyl is seeking a technically seasoned professional to embed inside client environments and make our AI agents work against data never prepared for them. You will solve a specific problem for each organization, using data such as CRMs, warehouses, and document archives.

You will partner with CTOs and Enterprise Data Strategists on each account, delivering measurable outcomes like leads written to CRM and pipelines running in production.