Data Product Engineer

Recruiting From Scratch•San Francisco, CA

21h•Onsite

About The Position

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.

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
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
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
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

Nice To Haves

Familiarity with modern multi-agent architectures, RAG pipelines, or AI orchestration frameworks is highly desirable
Candidates from top technical universities are preferred, though exceptional industry experience is equally valued

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

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