Role Description
You will work directly with healthcare customers, understand complex data challenges, build the solution, deploy it, and help turn successful customer implementations into scalable platform capabilities.
What You'll Work With
Python SQL Data Pipelines Batch Processing Structured & Unstructured Data HL7/FHIR PHI/HIPAA AWS/GCP/Azure REST APIs Data Integrations****
What You'll Do
- Own customer engagements from scoping through delivery
- Translate ambiguous requirements into working production solutions
- Build large-scale pipelines for EHR, claims, imaging, genomics, and other healthcare data
- Work directly with customer engineering teams and data partners
- Build last-mile solutions when the platform doesn't fully meet customer needs
- Identify repeatable patterns and help turn them into scalable product capabilities
- Work across the stack with a strong spike in data engineering
What We're Looking For
Strong data engineering experience at scale
Experience building batch data pipelines for large volumes of structured and unstructured data
Strong SQL and ETL skills
Customer-facing technical experience
Ability to own projects end-to-end
Experience as a founding engineer, early startup engineer, FDE, or similar high-ownership role
Working understanding of AI/ML training workflows
Healthcare data experience, especially PHI/HIPAA, HL7/FHIR, is a strong plus
Comfortable adapting quickly when customer requirements change
Ideal Background
We're especially interested in engineers coming from:
VC-backed FDE companies
Early-stage/high-growth startups
Big Tech with broad technical ownership
Data-heavy or healthcare technology environments
The strongest candidates are technical generalists who can go deep in data engineering and are comfortable talking directly with customers.
This Role Is For You If...
You enjoy solving problems that don't have a perfect specification.
You can walk into a customer environment, understand the problem, challenge assumptions when needed, and build something that actually works.
You’re comfortable moving quickly when a deal is live — including occasional nights or weekends when deadlines require it.
Not a Great Fit If...
Your AI experience is mostly surface-level
You prefer a strict 9-to-5 environment
You want to work only on one long-term product
You don't have strong hands-on data engineering experience
You haven't worked directly with customers or owned delivery end-to-end
Thanks & Regards
Wazeer Khan & Abbas Khan
Pay: $220,000.00 - $320,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Employee assistance program
- Employee discount
- Flexible schedule
- Flexible spending account
- Health insurance
- Health savings account
- Parental leave
- Professional development assistance
- Retirement plan
- Vision insurance
Application Question(s):
- Python • SQL • Data Pipelines • Batch Processing • Structured & Unstructured Data • HL7/FHIR • PHI/HIPAA • AWS/GCP/Azure • REST APIs • Data Integrations
- Strong data engineering experience at scale
- Experience building *batch data pipelines* for large volumes of structured and unstructured data
- Ability to own projects end-to-end
- Experience as a *founding engineer, early startup engineer, FDE, or similar high-ownership role*
- Working understanding of AI/ML training workflows
- Healthcare data experience, especially *PHI/HIPAA, HL7/FHIR*, is a strong plus
- Early-stage/high-growth startups
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.
Similar Roles
Get the FDE Pulse Brief
Weekly market intelligence for Forward Deployed Engineers. Job trends, salary data, and who's hiring. Free.