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Vecten

AI-native data platform for private capital

Senior Backend Engineer - Multiple Teams

Backend EngineeringConfirmed live in the last 24 hours
Full-timeRemote in PolandNo salary listed

About the Job

Requirements

  • At least 5 years of backend engineering experience, with strong, recent TypeScript production experience and experience with Nest.js or a comparable dependency-injection-based Node framework.
  • Experience building integration services or API gateways, including webhooks, signature-based authentication, retries, idempotency, circuit breakers, and third-party API adapters.
  • Experience with PostgreSQL and relational data modelling, including schema design and migrations.
  • Experience with multi-tenant systems or another domain where data isolation is a hard requirement, and the ability to test it explicitly.
  • Hands-on AWS experience with ECS/EKS or Lambda, SQS, S3, IAM, and Secrets Manager or Vault; ability to read and propose Terraform even if another team applies it.
  • Use AI tools such as Claude Code and Codex as a core part of delivery while reviewing every line that ships.
  • Ability to scope ambiguous requests, write a short design note, ask clients clarifying questions early, and deliver without heavy oversight.
  • Fluent English and clear, proactive communication with technical and non-technical stakeholders.

Responsibilities

  • Design and build the gateway service on the client's Nest.js-based internal framework and AWS, proposing infrastructure changes as Terraform pull requests for the client's DevOps team to apply.
  • Implement the webhook contract, including HMAC authentication in application code with secrets in Vault, IP allowlisting, ISO-8601 date handling, and policy-version-at-date-of-loss selection.
  • Build the tenant router and registry with composite resolution and well-defined failure behaviour.
  • Build the source adapter framework with a common interface and per-source authentication, timeouts, retries with backoff, and circuit breaking so one slow tenant source cannot degrade other tenants' webhooks.
  • Build the batch path with SFTP landing zones per tenant, file validation and quarantine, idempotent loads into a PostgreSQL policy store, snapshot retention, and freshness monitoring.
  • Define the canonical policy model and shared canonical-to-target mapper; take the first partner's mapping tables for coverage codes, deductible types, and roles through review with the client's claims expert.
  • Ship per-tenant observability, including structured logs, metrics, a Grafana dashboard, freshness and error-rate alerts, and an onboarding runbook.
  • Write isolation negative tests as a release gate, run failure-mode drills and end-to-end walkthroughs in the client's sandbox, and support the client's security review.
  • Collaborate directly with client engineers and domain experts across time zones, largely asynchronously; provide some availability in the Pacific Time timezone, no more than once a week.

Desired Qualifications

  • Insurance domain exposure, including policy administration systems, claims, first notice of loss, coverages and deductibles, and managing general agent/carrier structures.
  • Batch or file-based integration experience, including SFTP ingestion, schema validation, and quarantine patterns, or data-mapping-heavy work.
  • Regulated-data experience, including personally identifiable or protected health information handling, HIPAA or SOC 2 controls, and audit logging.
  • Experience with Grafana or OpenTelemetry-style observability.
  • Prior consulting or client-facing delivery experience.

About the Company

Vecten

AI-native data platform for private capital

Vecten provides AI-native data and technology solutions for high-stakes decisions in private capital and healthcare. Its four-layer approach starts with Vecten Compass for transformation, then Vecten Core to deploy an AI-native data platform in the client’s cloud, Vecten Edge to run ML models, LLM workflows, and AI agents, and Vecten Drive for ongoing operations with monthly subscriptions while ensuring clients own their data. The company differentiates itself by offering a fully productized, end-to-end stack that turns fragmented information into a unified data layer and applied AI across private equity and healthcare use cases. Its goal is to deliver measurable value—enabling faster, more informed decisions, smoother operations, and sustained value creation for clients.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Warsaw, Poland
Founded
2010

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