Backend Platform Engineer

Infinity Constellation

Backend Platform Engineer at Labrynth developing AI-powered platforms for regulatory compliance. Responsibilities include building APIs and integrating complex data models.

Posted 7/28/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in TypeScript backend engineering, including modular API development and PostgreSQL security and data modeling. Proficient in integrating identity and authorization systems while ensuring robust testing and operability across distributed systems.

Highest-signal resume keywords

TypeScript Backend EngineeringPostgreSQL Security and Data ModelingIdentity and Authorization IntegrationDistributed Work ExecutionPython Worker Integration

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Applicant Tracking System Keywords

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Hard Skills

TypeScriptNode.jsPostgreSQLFastifyJSON SchemaOpenAPIPydanticTDDIdempotencyConcurrency Control

Tools & Technologies

CognitoSQSOpenTelemetryTypeBoxUv

Industry Keywords

RESTOpenAPI ContractSchema-First ToolingRow-Level SecurityTransactional OutboxAdversarial Tenant-Isolation TestsAppend-Only LedgersAudit PathsService ContractsFailure Drills

Tech Stack

Tools & technologies

JavaScriptNode.jsPostgresPythonSQLSwitchingTypeScript

About the role

Key responsibilities & impact

Build the versioned REST/OpenAPI contract and modular TypeScript BFF, with stable success/error envelopes, generated TypeScript clients, and contract-drift CI gates.
Integrate Cognito identity with opaque application sessions, and implement admission, invitations, personal/team accounts, memberships, capabilities, explicit account switching, and guarded account conversions that preserve asset identity and history.
Implement the minimal separate operator admission service and audited break-glass workflows, keeping customer and operator identities, sessions, routes, roles, and audit paths independent.
Design PostgreSQL domain models, migrations, forced-RLS authorization, transaction-bound authorization contexts, and immutable account_id constraints, proving cross-account denial through BFF tests and direct runtime-role SQL tests.
Deliver the durable asynchronous operation path: idempotent acceptance, typed payment-disabled beta entitlements, transactional outbox, account-fair SQS dispatch, worker lease/heartbeat/fencing, result commit, retry, cancellation, and DLQ/redrive.
Implement durable progress delivery: append-only operation events, resumable SSE, and cursor polling with no lost or duplicated logical events.
Maintain usage, provider, and observability foundations: exactly-once logical usage ledgers, safe (customer-content-free) logs, metrics, and traces, and the worker and operation signals Platform dashboards need.
Support current-and-prior compatibility semantics across database, OpenAPI, events, queues, and worker callbacks, including expand/deploy/backfill/verify/contract changes and rollback.
Build private Python worker workflows and typed pydantic-ai agent boundaries, and hand over API documentation, ADRs, threat models, tests, fixtures, runbooks, and a dependency-aware plan for the next B2C vertical.

Requirements

What you’ll need

TypeScript backend engineering: strong Node.js and TypeScript experience building modular production APIs; Fastify, JSON Schema, generated OpenAPI, and schema-first tooling such as TypeBox strongly preferred.
PostgreSQL security and data modeling: advanced schema design, migrations, transactions, row-level security, database roles, composite foreign keys, append-only ledgers, and concurrency control.
Identity and authorization: integrating Cognito or another OIDC provider while keeping product admission, account membership, and capabilities in authoritative application state.
Distributed work execution: transactional outbox, SQS or comparable queues, idempotency, at-least-once delivery, leases, heartbeats, fencing tokens, cancellation, retries, and DLQ recovery.
Revisioned domain design: immutable revisions, compare-and-swap updates, ETags, lineage, state machines, and evidence-preserving lifecycle transitions.
Python worker integration: modern typed Python, uv, Pydantic, pydantic-ai, and clear service contracts between TypeScript application code and private Python workers.
AI trust boundaries: typed model tools and outputs, server-resolved authority, bounded retrieval context, citation validation, and fail-closed persistence of model proposals.
Testing and operability: TDD, contract and integration tests, adversarial tenant-isolation tests, failure drills, OpenTelemetry instrumentation, and end-to-end execution against realistic services.

Benefits

Comp & perks

High-impact work at the intersection of AI and critical infrastructure regulation
Direct customer exposure and a seat at the table when we decide what to build
Small team with outsized influence; your field learning shapes the product roadmap
Modern AI-native development environment (Claude Code, Cursor, multi-model orchestration)
Remote-first
Competitive compensation