Staff Backend Software Engineer, Lightfield

• 7+ years experience
• Strong software engineering fundamentals and substantial experience building backend systems
• A record of owning significant product-facing systems or ambiguous technical projects from design through production
• Strong judgment about data models, APIs, system boundaries, migrations, and incremental rollout
• Experience operating systems with real reliability, latency, throughput, and correctness requirements
• Comfort debugging across multiple layers of the stack, especially when product behavior and system behavior do not line up neatly
• Product orientation: you care about the customer-visible consequences of backend decisions, not only the elegance of the implementation
• The ability to make practical tradeoffs, communicate clearly, and create alignment without relying on formal authority

Desirable

• At Lightfield, the backend is not a layer beneath the product. It is the product's foundation
• Lightfield builds a living model of a company's customers from emails, calls, meetings, and other signals. It structures that raw history into customer-defined objects, attributes, relationships, and versioned values, then exposes the same underlying capabilities to the product UI, external APIs, automations, and agents
• Decisions about the data model, authorization, event propagation, and execution semantics directly determine what customers can do
• As a Software Engineer, Backend, you'll own those decisions for important product capabilities
• You'll start with an ambiguous customer or product problem, define the behavior and system boundaries, design the data model and APIs, sequence migrations, and carry the capability through rollout and production. Recent examples include record-level permissions, field history and audit, durable workflows, and consumption metering
• These foundations already operate at meaningful scale:
• Our Postgres fleet serves 5B+ queries a month — roughly 2,500 QPS steady state, with sustained spikes past 25,000 QPS — and database workload more than doubled last month
• Redis sustains ~50,000 commands per second behind a job platform that executes 10M+ background job runs a day across ~170 queues
• We ingest tens of millions of emails and calendar events a month
• Scale makes the product work technically serious: new abstractions must be fast, reliable, observable, and safe under real load. But this is not primarily a role for keeping the lights on
• It's a chance to define foundational pieces of an AI-native product while the architecture is still taking shape—and to see those decisions change what customers and agents can accomplish
• Own core product capabilities end to end—from customer requirement and behavioral semantics through data model, API, migration, rollout, and operation
• Design the shared abstractions used by Lightfield's UI, public API, agents, automations, and internal engineering teams
• Evolve a schema-flexible, graph-shaped data model on Postgres, where customers define objects, attributes, and relationships at runtime and values change over time
• Build systems for authorization, history, event propagation, durable execution, and metering that become visible parts of the customer experience
• Partner directly with product engineers, product leadership, and customers to turn ambiguous needs into practical backend architecture
• Make high-throughput Node.js services, Postgres query paths, APIs, queues, and background jobs fast, reliable, observable, and understandable
• Debug production behavior across application code, database execution, distributed workflows, and observability data rather than treating each layer in isolation
• Decide when a focused fix is enough and when the product needs a durable new primitive or architectural change
• Raise the technical bar through design leadership, code review, operational ownership, and clear engineering judgment
• What your first year could look like:
• The work is organized around consequential product problems rather than a fixed infrastructure lane. Projects you might own or extend include:
• Permissions: define and enforce record-level access across the product UI, REST API, search, dashboards, agent context, captured interactions, and exports—then migrate customers safely onto the model
• History and audit: make field and relationship changes queryable and trustworthy for customers, agents, APIs, and compliance-sensitive workflows
• Change propagation: evolve the transactional outbox that fans CRM mutations into search, summarization, automations, and downstream systems without losing ordering, attribution, or observability
• Durable work: build the execution model behind long-running workflows and automations, including retries, scheduling, versioning, debugging, and safe code execution
• Usage and billing: design metering primitives that connect product behavior to consumption limits, customer analytics, and billing
• Data and search evolution: ship zero-downtime changes across Postgres and search infrastructure while preserving correctness for a live, multi-tenant product
• You'll move among projects as priorities change, sometimes leading a small pod and sometimes contributing to one
• The constant is end-to-end ownership: understanding why the capability matters, making the architecture concrete, shipping it, and staying close to how it behaves for customers in production
• This role can be based in San Francisco or Cambridge. In San Francisco, you'd work from our HQ alongside the founders and most of the engineering team
• In Cambridge, you'd join an initial group of staff-level engineers at our new Kendall Square site, working alongside one of our most senior infrastructure engineers. We aim to build the site and organization around this group as the company scales
• Most companies separate product work from platform work: one team decides what customers should experience, and another builds the systems underneath it. At Lightfield, many of the most important product questions are backend questions.
• What does a customer record mean when its schema can change at runtime? How should permissions apply to an agent, an automation, a search result, or a meeting captured tomorrow? How do you make historical state, background execution, and customer-facing APIs reliable enough to become product primitives?
• You'll get to answer questions like these while the answers are still being formed. The abstractions you design will be used by customers, product engineers, external developers, and agents—and will shape which products Lightfield can build next
• The appeal is not just technical depth or scale. It's the chance to own consequential pieces of the product, from the customer problem to the production system, at a stage when individual engineering judgment still has outsized influence