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About the Role

We are seeking a staff-level engineer with expertise in data infrastructure to build the next generation of our data systems. This role involves working across backend systems, infrastructure, and product-facing data challenges, with a focus on evolving our pragmatic data foundation into best-practice architecture. You will shape the technical direction, abstractions, and engineering practices for our data systems as the company grows.

Responsibilities

Scale the analytics engine behind customer-facing dashboards, addressing query performance, workload isolation, read architecture, and observability.
Design ingestion paths, event models, schemas, and query patterns for moving data into search, dashboards, and history with freshness and correctness guarantees.
Evolve our schema-flexible, graph-shaped data model to ensure efficient querying of customer-defined objects, attributes, and relationships.
Build foundations for historical reporting and auditability, including attribute versioning, relationship history, and change capture.
Develop reliable data systems for usage metering, pipeline generation, and AI evaluation.
Determine when to leverage existing architecture and when to introduce new analytical, streaming, or workflow systems.
Set the technical direction, abstractions, ownership boundaries, and engineering practices for data systems.

Requirements

Strong software engineering fundamentals.
Experience owning production data systems with user-facing consequences related to query plans, replication lag, backfills, data freshness, schema evolution, or data correctness.
Comfort debugging across multiple layers of the stack.
Good judgment regarding tactical fixes versus durable platform or architecture changes.
Product orientation and care for how data infrastructure decisions affect customers, users, and engineering velocity.
Clear communication, strong ownership, and a bias toward practical tradeoffs.

Skills

Postgres
Redis
Typesense
BullMQ
Change data capture
Event modeling
Schema design
Query performance
Data freshness guarantees
Transactional workloads
Analytical workloads
Entity-attribute-value model
Graph-shaped data model
Attribute versioning
Relationship history
Data warehousing
APIs
Queues
Distributed systems
Observability
Incident response
Service ownership
Production debugging
Data for ML/AI systems
Evaluation harnesses
Data-quality tooling

Location

San Francisco
Cambridge

Work Type

Onsite
Hybrid

Experience Level

Staff-level

Benefits

Competitive salary
Meaningful early equity
Health insurance (medical, dental, vision)
3 weeks of PTO
11 paid company holidays
Winter holiday break
3 months of paid family leave
Wednesdays work from home
Regular team dinners, events, offsites, and retreats
401k plan
Commuter stipend
Lunch stipend

About the Company

Lightfield is an AI-native CRM that assembles itself from your email, calendar, and meetings, capturing every interaction and turning it into organized context.
We are rethinking CRM from first principles, building a system that learns from how companies work, adapting, automating, and surfacing insights.
We are backed by Greylock, Lightspeed, and Coatue.
Our founders previously built Tome, a generative AI presentation product used by over 25 million people.
Our team has prior experience at Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.