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Senior Backend / Data Platform Engineer

This role helps build Lucy, the proactive AI coach from Lucy Labs that lives on your desktop as a cloud-backed app, while the product is in development with design partners.

Owns evidence ingestion and the lifecycle backbone under everything else.

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Planned work

About the role

At Lucy Labs, this role owns the purpose described below.

The Senior Backend / Data Platform Engineer owns Lucy's evidence ingestion and lifecycle backbone: landing-zone metadata, object references, idempotency, replay, deletion handles, data contracts, and the services that carry captured evidence safely into behavior inference, evaluation, knowledge graph, coaching, and analytics systems.

This role is narrower and more trust-critical than a generic backend engineer. It is responsible for making captured work evidence reliable, replayable, auditable, and deletable.

The mission

At Lucy Labs, this role's mission is defined by the outcome and work below.

Build backend and data-platform foundations that:

Ingest desktop, browser, connector, and user-correction evidence safely
Preserve provenance and object references across derived data products
Make replay, backfill, deletion, and retention operationally reliable
Give privacy/security and eval systems stable contracts to build on
Scale from design-partner proof to early enterprise deployment

What you'd own

At Lucy Labs, this role turns its mission into concrete responsibilities in each area.

1. Evidence Ingestion and Data Contracts

For 1. Evidence Ingestion and Data Contracts, Lucy Labs expects this role to own the responsibilities below.

Design ingestion services for screen/app/window/tool evidence and user corrections
Define typed contracts for raw evidence, normalized events, derived actions, and inference candidates
Build idempotency, deduplication, ordering, and replay semantics
Partner with Desktop/Client Capture on local buffering and upload boundaries

2. Lifecycle, Retention, and Deletion

For 2. Lifecycle, Retention, and Deletion, Lucy Labs expects this role to own the responsibilities below.

Implement retention and deletion handles that survive across downstream systems
Track derived-data lineage so privacy actions can propagate correctly
Build audit trails for data movement and policy application
Support enterprise data residency and customer-specific policy requirements

3. Platform Reliability

For 3. Platform Reliability, Lucy Labs expects this role to own the responsibilities below.

Build APIs, queues, storage patterns, and jobs that remain observable and recoverable
Design backfill and migration paths for evolving Work Modeling schemas
Own performance, latency, and cost characteristics of evidence pipelines
Create operational runbooks and failure-mode tests

4. Cross-Functional Partnership

For 4. Cross-Functional Partnership, Lucy Labs expects this role to own the responsibilities below.

Work tightly with Privacy/Security/Trust on controls and threat models
Work with Data/Evaluation on labeling datasets and regression corpora
Work with KG/Ontology on stable identifiers and relationship update rules
Work with AI Platform/MLOps on inference inputs, model versions, and eval execution

What success looks like

Lucy Labs defines these milestones as role outcomes, not metrics for measuring the person.

60 days: Evidence ingestion architecture and first contracts are implemented
90 days: Replay, deletion, and lineage primitives are demonstrable end to end
6 months: Design-partner evidence pipelines are reliable enough for eval and correction loops
12 months: Enterprise-scale ingestion is observable, auditable, and cost-controlled

Experience and fit

Lucy Labs looks for the essential experience listed here and treats the rest as helpful, not an automatic barrier.

Must have

5+ years backend or data platform engineering experience
Strong Python, TypeScript, or similar production backend experience
PostgreSQL and data-modeling depth, including migrations and performance tuning
Experience with event pipelines, queues, idempotency, or replayable systems
Practical judgment about privacy, auditability, and operational failure modes

Nice to have

Experience with evidence/event pipelines, observability, or process mining data
Experience with GDPR deletion, retention, or enterprise data governance
Familiarity with knowledge graphs, vector search, or ML/eval datasets
Startup or 0-to-1 data-platform experience

How you work

Lucy Labs looks for these working traits alongside technical experience.

Role DNA

Lucy Labs evaluates these traits as part of the fit for this role.

Data-contract disciplined
Reliability-minded
Privacy-aware
Comfortable with ambiguous event semantics
Strong partner to product and trust teams

Next step

Apply for this role

The Lucy Labs application form opens with this role already selected. You can review the message before sending it.

Apply for this role

Frequently asked questions

Is this role open at Lucy Labs?

Yes. Lucy Labs confirmed this role is open on 25 August 2026.

Where does Lucy Labs base this role?

Lucy Labs bases this role in Madrid, Spain. The exact working arrangement is confirmed during the application conversation.

What does this role own at Lucy Labs?

At Lucy Labs, this role has one central responsibility: Owns evidence ingestion and the lifecycle backbone under everything else. The full description sets out the mission, responsibilities, and relevant experience.

How do I apply to Lucy Labs?

At Lucy Labs, use the application form. The role is selected automatically, and you can review it before sending.