Remote Backend Engineer

IntePros

$110K — $130K *
US-AnywhereRemote in United States
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of backend development experience with languages such as Java, Python, .NET, Node.js, or TypeScript.
  • Strong understanding of API design, microservices, and distributed systems architecture.
  • Familiarity with AWS cloud services and deployment best practices.
  • Experience in developing automated tests and implementing software quality gates.
  • Ability to work with AI-assisted development tools and methodologies.
  • Knowledge of designing ontologies, taxonomies, and knowledge graphs.

Responsibilities

  • Design, build, and operate cloud-native backend services and APIs.
  • Implement business logic and service orchestration for project workstreams.
  • Develop integrations with enterprise and third-party systems.
  • Leverage AI tools to accelerate development while ensuring quality.
  • Create automated tests as part of the software delivery lifecycle.
  • Contribute to defining API standards and CI/CD practices.
  • Own the monitoring and incident response for delivered services.

Benefits

  • Remote work flexibility to maintain work-life balance.
  • Access to modern AI-assisted development tools.
  • Opportunities for professional growth in a scaling enterprise.
  • Collaborative work environment with cross-functional teams.
Full Job Description
Remote Backend Engineer

Our client, a growing enterprise technology organization, is seeking a Backend Engineer to build and operate core APIs, services, orchestration layers, integrations, and business capabilities. This role combines strong software engineering discipline with modern AI-assisted development practices to deliver secure, scalable, resilient services from design through production operation.

Key Responsibilities:
  • Design, build, test, deploy, and operate cloud-native backend services, APIs, workflows, and integration capabilities.
  • Implement business logic, orchestration services, domain services, event-driven patterns, and service composition required by project workstreams.
  • Develop integrations with enterprise systems, third-party platforms, data services, pricing/underwriting capabilities, and AI/agent services.
  • Leverage AI coding agents and engineering copilots to accelerate development while maintaining strong review, testing, and production quality practices.
  • Create automated unit, integration, contract, regression, and performance tests as part of the delivery lifecycle.
  • Contribute to API standards, reusable patterns, golden paths, CI/CD pipelines, infrastructure automation, and service reliability practices.
  • Own production readiness, monitoring, incident response, defect remediation, and continuous improvement for delivered services.
  • Collaborate with Analysts and Product Owners to ensure requirements, contracts, and acceptance criteria are clear and technically executable.
Preferred Skills:
  • Backend development experience with Java, Python, .NET, Node.js, TypeScript, or equivalent enterprise technologies.
  • API-first design, microservices, service orchestration, event-driven architecture, and distributed systems patterns.
  • AWS cloud services, containers, CI/CD, infrastructure as code, secrets management, and automated deployment practices.
  • Experience with contract testing, automated quality gates, performance tuning, observability, and production support.
  • Comfortable working in an AI-assisted delivery environment where engineers guide, review, harden, and operationalize agent-generated outputs.
  • Design and maintain ontologies, taxonomies, business vocabularies, semantic models, and concept relationships across domains.
  • Develop knowledge graphs, entity relationships, metadata structures, and mappings that allow agents and systems to reason across business concepts.
  • Engineer AI agent patterns, retrieval-augmented generation pipelines, prompt strategies, orchestration flows, evaluation frameworks, and reusable AI components.
  • Generative AI, LLM application development, prompt engineering, agent orchestration, and RAG architecture.
  • Ontology modeling, taxonomy development, knowledge graphs, semantic technologies, and metadata design.
  • Python, ML/AI frameworks, vector databases, semantic search engines, and data integration patterns.
What Sets This Role Apart
  • Not a narrow coder role - you'll help shape service architecture and own outcomes through production.
  • Opportunity to reduce system dependencies through strong contracts and self-service platform patterns.


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