Remote Senior Forward-Deployed AI Engineer

afresh; United States; Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

Retirement matching

Equity

Home-office and coworking support

Professional development funding

Monthly wellness stipend

Job summary

afresh is seeking a Senior Forward Deployed Engineer to blend customer-facing delivery with platform engineering. You will partner with enterprise grocery clients to integrate complex data, build production-grade AI systems, and translate deployments into reusable infrastructure and tooling that accelerates future projects.

You will lead architecture discussions, design data pipelines, and implement retrieval-augmented generation, tool use, and evaluation workflows.

Qualifications

• At least 3 years of experience building production software and data systems.
• Ability to turn ambiguous problems and complex data environments into practical architectures.
• Hands-on experience with real LLM or agent applications, including retrieval-augmented generation.
• Strong data-engineering experience with production pipelines and cloud data platforms such as Databricks, BigQuery, Snowflake.
• Comfort switching between customer-facing collaboration and focused platform development.

Responsibilities

• Collaborate with customer technical teams to define scope and design architecture.
• Integrate with cloud and data platforms, build reliable pipelines, and clean data.
• Design and deploy production-grade LLM and agent systems with retrieval and tooling.
• Strengthen platform capabilities like knowledge graphs, ontologies, and serving infra.
• Build observability tools to measure accuracy, latency, and cost.
• Create reusable interfaces and components while feeding learnings back to the platform.

Job description

afresh is seeking a Senior Forward Deployed Engineer to blend customer-facing delivery with platform engineering. You will partner with enterprise grocery clients to integrate complex data, build production-grade AI systems, and translate deployments into reusable infrastructure and tooling that accelerates future projects.

You will lead architecture discussions, design data pipelines, and implement retrieval-augmented generation, tool use, and evaluation workflows.