Job description

WHO WE ARE: Materialize is the live context layer for AI agents and applications. Materialize lets engineering teams use SQL to transform siloed operational data into up-to-the-second, trustworthy views into any element of their business — delivering fresh context to AI agents, interactive search pipelines, and enabling low-latency, event-driven architectures for microservices and core business processes. Materialize is trusted by Notion, Bilt Rewards, and Crane Worldwide Logistics to solve their most pressing operational data challenges while building a live data foundation for their AI transformation. Our team spans the US (NYC headquarters), Canada, and EMEA. INVESTORS: Kleiner Perkins, Redpoint Ventures and Lightspeed Venture Partners. ROLE OVERVIEW As Materialize's first Forward Deployed Engineer, you embed with a small number of our most strategic customers and help them build end-to-end solutions with Materialize at the core. You'll join our Go-To-Market organization, partnering with Account Executives and Field Engineering to take engineering-led organizations, customers like Notion, General Mills, Bilt Rewards, and Crane Worldwide Logistics, from signed contract to live deployment, and then to the use case after that. You own delivery end to end: architecture, pipelines, integrations, and production rollout. In your first year, you'll write the SQL and integration code that gets customers into production and beyond, and build the reference architectures and delivery patterns the FDE team will run on. You'll have a direct line to Product and Engineering, and what you learn in customer environments will help shape the roadmap. This role is for someone who is comfortable owning an ambiguous, high-stakes problem inside someone else's codebase, and who wants to define a function rather than inherit one. This role is based in our NYC office near Astor Place, with a minimum of 3 days per week in person. Travel 30–50% during active customer engagements, and less between them. You'll be onsite when it matters most: kickoffs, critical launches, and production cutovers. RESPONSIBILITIES - Own end-to-end technical delivery for a small number of flagship accounts, from architecture design through production cutover and beyond - Build the connectors, SQL-based views, and integrations that put Materialize into production — Postgres and MySQL CDC, Kafka, Kinesis, dbt, BI tools, and customer applications - Plan and run migrations from existing systems, including dual writes and controlled cutover - Design Materialize architectures for real-time use cases: fraud detection, dynamic pricing, operational dashboards, context for AI agents, and event-driven pipelines - Write and debug complex SQL and streaming pipelines directly in customer environments, alongside their engineering teams - Support customers through implementation, production hardening, and critical launches - Build the reusable layer (reference architectures, internal tooling, and implementation patterns) that makes each deployment faster than the last - Translate what you see in the field into clear product and engineering feedback: friction points, missing features, and the workarounds customers keep reaching for - Act as a trusted technical advisor on architecture, scaling, and best practices for real-time data - Travel roughly 20–25% for onsite customer engagements and key industry events WHAT WE’RE LOOKING FOR - 5+ years of engineering experience, including 1+ years in a post-sales, customer-facing role (e.g., forward deployed engineering, solutions engineering, solutions architecture, or technical consulting) with a track record of owning complex enterprise implementations - Strong SQL and a solid understanding of modern data architectures: relational databases, event streaming, and change data capture - Hands-on experience with streaming or event-driven systems (Kafka, Debezium/CDC, Kinesis, Flink, Spark Streaming, or similar) - You write code. Proficiency in at least one of Python, Java, or TypeScript for building integrations and tooling - Familiarity with cloud infrastructure (AWS, GCP, or Azure) and containerized environments - You've taken systems from prototype to production in someone else's environment, including the unglamorous parts: performance tuning, failure modes, monitoring, and handoff - Comfortable owning ambiguous, high-stakes technical problems with incomplete information, and moving without a large support structure - Excellent written and verbal communication: you can translate deeply technical trade-offs for both engineers and executives, and you leave behind designs and runbooks that outlive the engagement - Experience with another streaming SQL engine or a modern data warehouse (Snowflake, BigQuery, Redshift) is a plus - Production experience with AI agents or LLM applications, especially the context layer that feeds them fresh, trustworthy data, is a plus - Experience at a fast-growing startup, or as an early member of an FDE or professional services function, is a plus Location: NYC (hybrid, minimum 3 days/week at our Astor Place HQ) Salary: $180,000 - $225,000 USD/year plus additional variable bonus and equity in addition to a full range of medical, financial, and/or other benefits. The base pay offered may vary depending on job-related knowledge, skills, and experience. The salary range provided in this job description should not be considered a guarantee or commitment. The actual compensation offered may vary based on individual qualifications objectively assessed during the application and interview process, including but not limited to the candidate’s: - Qualifications and relevant work experience - Educational background and credentials - Relevant skills and certifications - Geographic location - Market demands Materialize reserves the right to adjust the salary range based on the candidate's specific circumstances and the overall compensation package. We understand it takes a diverse team of highly intelligent, passionate, curious, and creative people to develop the exceptional product we are building. Our dynamic team has incredible perspectives to share, just as we know you do, and we take great pride in being an equal opportunity employer.

Requirements

Must-haves

Kleiner Perkins, Redpoint Ventures and Lightspeed Venture Partners.
Own end-to-end technical delivery for a small number of flagship accounts, from architecture design through production cutover and beyond
Build the connectors, SQL-based views, and integrations that put Materialize into production — Postgres and MySQL CDC, Kafka, Kinesis, dbt, BI tools, and customer applications
Plan and run migrations from existing systems, including dual writes and controlled cutover
Design Materialize architectures for real-time use cases: fraud detection, dynamic pricing, operational dashboards, context for AI agents, and event-driven pipelines
Write and debug complex SQL and streaming pipelines directly in customer environments, alongside their engineering teams
Support customers through implementation, production hardening, and critical launches
Build the reusable layer (reference architectures, internal tooling, and implementation patterns) that makes each deployment faster than the last
Translate what you see in the field into clear product and engineering feedback: friction points, missing features, and the workarounds customers keep reaching for
Act as a trusted technical advisor on architecture, scaling, and best practices for real-time data
Travel roughly 20–25% for onsite customer engagements and key industry events
Strong SQL and a solid understanding of modern data architectures: relational databases, event streaming, and change data capture
Hands-on experience with streaming or event-driven systems (Kafka, Debezium/CDC, Kinesis, Flink, Spark Streaming, or similar)
You write code. Proficiency in at least one of Python, Java, or TypeScript for building integrations and tooling
Familiarity with cloud infrastructure (AWS, GCP, or Azure) and containerized environments
You've taken systems from prototype to production in someone else's environment, including the unglamorous parts: performance tuning, failure modes, monitoring, and handoff
Comfortable owning ambiguous, high-stakes technical problems with incomplete information, and moving without a large support structure
Excellent written and verbal communication: you can translate deeply technical trade-offs for both engineers and executives, and you leave behind designs and runbooks that outlive the engagement
Location: NYC (hybrid, minimum 3 days/week at our Astor Place HQ)
Qualifications and relevant work experience
Educational background and credentials

Nice-to-haves

Experience with another streaming SQL engine or a modern data warehouse (Snowflake, BigQuery, Redshift) is a plus
Production experience with AI agents or LLM applications, especially the context layer that feeds them fresh, trustworthy data, is a plus
Experience at a fast-growing startup, or as an early member of an FDE or professional services function, is a plus

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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