Staff Forward Deployed Engineer

afresh; United States; Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Remote work access

Medical/Dental/Vision coverage

Equity for eligible employees

401(k) with company matching

Home-office support

Coworking allowances

Professional development funding

Wellness stipend

Flexible paid time off

Job summary

afresh is seeking a staff-level engineer who alternates between customer-embedded delivery and platform development. The role involves integrating AI systems into complex enterprise data environments, building production-grade pipelines and data products, then turning field lessons into reusable infrastructure for future deployments.

This is hands-on, ambiguous 0-to-1 work suited to someone comfortable switching between architecture, implementation, customer collaboration, and platform

Qualifications

• Five+ years of experience building production software and data systems.

Responsibilities

• Work with customer technical teams to define data sources, architecture, delivery scope, and the path from initial concept to production.

Skills

Production software

Data systems design

LLM/agent systems

Customer collaboration

Cloud data platforms

Tools

Databricks

BigQuery

Snowflake

Job description

Role overview

Staff-level engineer who alternates between customer-embedded delivery and platform development. The role involves integrating AI systems into complex enterprise data environments, building production-grade pipelines and data products, then turning field lessons into reusable infrastructure for future deployments. This is hands-on, ambiguous 0-to-1 work suited to someone comfortable switching between architecture, implementation, customer collaboration, and platform ownership.

Responsibilities

• Work with customer technical teams to define data sources, architecture, delivery scope, and the path from initial concept to production.
• Integrate with cloud and data platforms, build reliable pipelines, and transform inconsistent enterprise data into trustworthy data products.
• Design and ship production-ready LLM and agent systems, including retrieval, tool use, agentic workflows, data-quality agents, and analytics agents.
• Develop shared knowledge and grounding infrastructure such as knowledge graphs, ontologies, retrieval layers, agent frameworks, and serving systems.
• Build evaluation, tracing, and operational tooling to measure accuracy, hallucination rates, latency, cost, and overall system quality.
• Replace one-off customer implementations with clean interfaces and reusable components that improve future deployments.

Requirements

• At least five years of experience building production software and data systems.
• Strong engineering judgment and the ability to turn ambiguous requirements and messy data landscapes into workable architectures.
• Demonstrated experience building real-world LLM or agent systems using retrieval, RAG, or tool-use patterns.
• Solid data-engineering experience, including production pipelines, enterprise data modeling, and modern cloud data platforms such as Databricks, BigQuery, Snowflake, or similar.
• Comfort working directly with customer engineering and data teams through technical workshops, explanations, and delivery ownership.
• Ability to move effectively between customer-facing work and focused platform engineering.

Benefits and work setup

• Remote work is available for employees residing in specified U.S. states, with some customer work potentially requiring on-site engagement.
• Medical, dental, and vision coverage, with substantial premium support, plus mental health services.
• Competitive compensation, equity for eligible U.S. employees, and a 401(k) program with company matching.
• Home-office support, coworking allowances, professional development funding, wellness and telecommunications stipends, and flexible paid time off.