Data Product Engineer

Recruiting From Scratch; San Francisco (CA); On-site; USD 230,000 - 280,000; Full time

Benefits offered by this job

Founding role

Onsite in San Francisco

Competitive equity

Job summary

Recruiting from Scratch in San Francisco, CA is looking for a Data Product Engineer to own the complete data layer powering our platform. This is an on-site, founding role with significant ownership, working with AI-native data systems and enterprise data sources.

You will build end-to-end data pipelines, ingest external data, and deliver production-grade infrastructure for AI agents, while collaborating with customers and product teams to solve strategic data problems.

Qualifications

• 5–8 years of professional software or data engineering experience.
• Experience building and operating production data systems end-to-end.
• Experience owning data platforms from ingestion through deployment.
• Experience at high-growth startups or rapidly scaling technology companies.
• Strong product mindset with the ability to connect technical decisions to customer value.
• Experience working with AI-native products or modern machine learning systems.
• Comfortable operating independently without established processes or playbooks.
• Demonstrated ownership of production infrastructure, reliability, monitoring, and maintenance.

Responsibilities

• Build and own the company's end-to-end data platform from ingestion through production deployment.
• Work directly with enterprise customers to identify high-value external data sources and new product opportunities.
• Design, build, and operate production data pipelines for structured and unstructured datasets.
• Integrate legal records, financial documents, insurance filings, PDFs, and other complex enterprise data into the platform.
• Develop scalable ingestion, extraction, transformation, and orchestration systems supporting AI agents.
• Build evaluation harnesses to monitor data quality, agent performance, and production reliability.
• Design search infrastructure enabling fast, accurate retrieval for LLM-powered applications.
• Build data products that expose clean, production-ready information directly to AI agents and customers.
• Own schema evolution, monitoring, pipeline reliability, and production maintenance.
• Collaborate closely with product, engineering, and customers to translate ambiguous business problems into scalable technical solutions.
• Build AI-powered workflows using modern LLMs, retrieval systems, and agent frameworks.
• Establish engineering best practices across data architecture, testing, deployment, and reliability.
• Operate with founder-level ownership in a fast-moving startup environment while helping define the company's long-term data strategy.

Skills

Python

SQL

Data pipelines

AI-enabled workflows

Ownership

Customer empathy

Communication

Ambiguity tolerance

Education

Bachelor's or higher in CS/Engineering/Math

Tools

APIs

Retrieval systems

LLM workflows

Job description

Who is Recruiting from Scratch:

Recruiting from Scratch is a premier talent firm that focuses on placing the best product managers, software, and hardware talent at innovative companies. Our team is 100% remote and we work with teams across the United States to help them hire.

Data Product Engineer

Location - San Francisco, CA (On-site -- 5 Days Per Week)

Compensation - $230,000 -- $280,000 Base + Competitive Equity

Visa - US Citizens & Green Card Holders Only (No Visa Sponsorship)

Company Stage - Seed ($10M Raised)

Industry - Artificial Intelligence, Enterprise AI, Data Infrastructure, Agentic AI, Insurance Technology, LLM Platforms

About the Company

Effective AI is building the operating system for the insurance industry by transforming fragmented enterprise knowledge into trusted, AI-native workflows.

The platform combines large language models, structured data, retrieval systems, and multi-agent architectures to help insurance organizations reason over complex documents, regulations, filings, legal records, and operational knowledge with significantly greater speed and accuracy.

Backed by Lightspeed and Valor with a $10M seed round, Effective AI is one of the fastest-growing applied AI startups tackling one of the world's largest industries---a $6 trillion insurance market. The company is building production AI systems focused on long-context reasoning, formal verification, retrieval, and multi-agent coordination while working directly with customers solving real operational problems.

As the company's first Data Product Engineer, you'll own the complete data layer powering the platform---from ingesting raw external data sources to building production-grade pipelines, evaluation systems, retrieval infrastructure, and customer-facing product experiences consumed by AI agents.

This is a rare opportunity to become the founding data engineering leader at an AI-native startup, combining product engineering, backend development, data infrastructure, and applied AI into one highly impactful role.

What You'll Do

• Build and own the company's end-to-end data platform from ingestion through production deployment
• Work directly with enterprise customers to identify high-value external data sources and new product opportunities
• Design, build, and operate production data pipelines for structured and unstructured datasets
• Integrate legal records, financial documents, insurance filings, PDFs, and other complex enterprise data into the platform
• Develop scalable ingestion, extraction, transformation, and orchestration systems supporting AI agents
• Build evaluation harnesses to monitor data quality, agent performance, and production reliability
• Design search infrastructure enabling fast, accurate retrieval for LLM-powered applications
• Build data products that expose clean, production-ready information directly to AI agents and customers
• Own schema evolution, monitoring, pipeline reliability, and production maintenance
• Collaborate closely with product, engineering, and customers to translate ambiguous business problems into scalable technical solutions
• Build AI-powered workflows using modern LLMs, retrieval systems, and agent frameworks
• Establish engineering best practices across data architecture, testing, deployment, and reliability
• Operate with founder-level ownership in a fast-moving startup environment while helping define the company's long-term data strategy

Ideal Candidate Background

Experience Requirements

• 5--8 years of professional software or data engineering experience
• Experience building and operating production data systems end-to-end
• Experience owning data platforms from initial ingestion through production deployment
• Experience at high-growth startups or rapidly scaling technology companies
• Experience building systems through both early-stage development and production scale
• Strong product mindset with the ability to connect technical decisions to customer value
• Experience working with AI-native products or modern machine learning systems
• Comfortable operating independently without established processes or playbooks
• Demonstrated ownership of production infrastructure, reliability, monitoring, and maintenance
• Leadership potential with interest in growing into ownership of an engineering function

Technical Requirements

• Expert Python engineering experience
• Strong SQL and relational database expertise
• Deep experience building production data pipelines and orchestration systems
• Experience with large-scale unstructured document processing (PDFs, filings, legal records, financial documents)
• Experience building AI-powered workflows using LLMs, retrieval systems, or agent frameworks
• Experience with evaluation frameworks, testing infrastructure, or model quality systems
• Experience designing scalable data architectures supporting production applications
• Strong backend software engineering fundamentals
• Experience integrating external APIs and complex third-party data sources
• Experience building production search infrastructure or retrieval systems preferred
• Familiarity with modern multi-agent architectures, RAG pipelines, or AI orchestration frameworks is highly desirable

Education

• Bachelor's or higher degree in Computer Science, Engineering, Mathematics, Physics, Electrical Engineering, or another STEM discipline preferred
• Strong technical foundation with demonstrated engineering excellence
• Candidates from top technical universities are preferred, though exceptional industry experience is equally valued

Soft Skills

• Exceptional product thinking
• Strong customer empathy
• Excellent systems thinking
• High ownership mentality
• Strong communication skills
• Ability to simplify complex technical concepts
• Comfortable working through ambiguity
• Strong execution orientation
• Collaborative, low-ego mindset
• Passion for building foundational AI infrastructure
• Curiosity around emerging AI technologies and modern engineering workflows

Compensation & Benefits

• Base Salary: $230,000 -- $280,000
• Competitive Equity Package
• Founding Data Product Engineer opportunity
• High ownership with direct influence over product architecture
• Work alongside experienced AI researchers and engineering leaders
• Opportunity to build foundational infrastructure powering enterprise AI agents
• Exposure to cutting-edge LLM systems, multi-agent architectures, and retrieval infrastructure
• Well-funded Seed-stage company backed by Lightspeed and Valor
• Significant career growth with opportunity to build and lead the future data organization
• Work onsite with a highly collaborative engineering team in San Francisco

Why Join

This is an opportunity to become the first Data Product Engineer at one of the most ambitious applied AI startups in enterprise software.

You’ll build the foundational data platform powering intelligent AI agents that reason over some of the world's most complex enterprise information, while helping define how production AI systems consume, validate, and reason over trusted data.

If you enjoy building production data systems, owning products from zero to one, working directly with customers and operating at the intersection of data engineering, backend systems, and applied AI, this role offers exceptional ownership, technical depth, and long-term impact.