Senior Backend Engineer

Senior Backend Engineer – SaaS & AI Integrations

Experience: Minimum 7+ Years
Employment Type: Full-Time
Work Arrangement: Remote
Seniority Level: Senior

About the Role

We are seeking an experienced Senior Backend Engineer to design, build, secure, integrate, and scale backend services for a complex multi-tenant SaaS platform with AI-enabled capabilities.

This is a hands-on senior engineering position requiring strong experience with backend architecture, APIs, distributed systems, PostgreSQL, cloud infrastructure, security, and production AI integrations.

You will be expected to own backend functionality from technical design through implementation, testing, deployment, observability, and production readiness.

We are specifically looking for engineers who have built real production systems. Experience limited primarily to basic CRUD applications, tutorials, prototypes, or simple API wrappers will not meet the requirements for this position.

Key ResponsibilitiesBackend Engineering & Architecture

• Design and develop scalable, secure, production-grade backend services.
• Build modular and maintainable backend architectures capable of supporting complex SaaS workflows.
• Translate product and technical requirements into reliable backend implementations.
• Design service boundaries, business logic, state transitions, validation rules, and failure handling.
• Identify architectural weaknesses and propose technically sound solutions.
• Participate in architecture and code reviews.
• Take ownership of backend features through production deployment and validation.

API Design & Development

• Design and implement secure REST APIs and service-to-service interfaces.
• Define clear request/response contracts, validation, error handling, and versioning strategies.
• Build idempotent APIs where required.
• Implement pagination, filtering, rate limiting, retries, and appropriate timeout behavior.
• Maintain API documentation using OpenAPI/Swagger.
• Ensure frontend and external integrations consume stable, documented API contracts.
• Design APIs that remain reliable under concurrency and failure conditions.

Multi-Tenant SaaS Engineering

• Build backend services for secure multi-tenant SaaS environments.
• Enforce tenant context and authorization throughout request processing.
• Prevent cross-tenant data leakage and privilege escalation.
• Implement role- and permission-based authorization.
• Design safe administrative and privileged operations.
• Understand the difference between authentication, authorization, tenant isolation, and application-level policy enforcement.

AI & LLM Integrations

• Design and implement production integrations with AI/LLM platforms and APIs.
• Build secure backend services that invoke and orchestrate AI capabilities.
• Integrate AI functionality into existing application workflows rather than treating AI as an isolated feature.
• Implement structured outputs, validation, retries, timeouts, fallbacks, and failure handling for AI services.
• Design AI provider abstraction where appropriate.
• Implement usage tracking, token/cost controls, rate limits, and observability for AI integrations.
• Securely manage AI provider credentials and secrets.
• Prevent AI-generated output from directly performing unauthorized or sensitive application actions.
• Implement human or system approval controls where appropriate.
• Evaluate and mitigate prompt injection, unsafe tool invocation, sensitive-data exposure, and cross-tenant AI risks.
• Work closely with AI/ML engineers when integrating internally developed AI capabilities.

Simply having called OpenAI, Claude, Gemini, or another LLM API from an application does not constitute sufficient AI integration experience for this position.

Candidates should be able to explain how they made AI functionality secure, observable, reliable, scalable, and appropriate for production.

Database & Data Layer

• Build backend services using PostgreSQL and other appropriate data technologies.
• Write efficient production-quality SQL.
• Work with transactions, constraints, indexing, locking, and concurrency.
• Implement safe data-access patterns for multi-tenant applications.
• Work closely with database engineering teams on schemas and migrations.
• Prevent backend services from bypassing database security or integrity controls.
• Diagnose database-related application performance problems.

Security & Governance

• Implement secure authentication and authorization patterns.
• Apply least-privilege principles across services.
• Protect sensitive data and credentials.
• Implement secure secrets management practices.
• Build auditable backend operations.
• Apply input validation and appropriate API security controls.
• Understand common API and application security vulnerabilities.
• Support enterprise security and compliance requirements.
• Participate in security reviews and remediation activities.

Distributed Systems & Reliability

• Design systems that handle retries, partial failures, duplicate requests, and concurrency safely.
• Implement idempotency where required.
• Design asynchronous and event-driven processing.
• Work with queues, events, background workers, and scheduled processing.
• Implement appropriate retry and dead-letter strategies.
• Understand eventual consistency and transactional boundaries.
• Build failure isolation into critical backend workflows.
• Prevent one failing dependency from unnecessarily destabilizing other services.

Integrations

• Design and implement integrations with third-party APIs and enterprise services.
• Work with webhooks, OAuth, API keys, service credentials, and external identity providers.
• Implement secure credential storage and rotation practices.
• Handle external provider failures, retries, rate limits, duplicate callbacks, and timeout conditions.
• Build reconciliation mechanisms where external and internal state may diverge.
• Maintain traceability across external integrations.

Testing & Quality

• Write unit, integration, and service-level tests.
• Test success, failure, authorization, concurrency, and edge cases.
• Participate in automated API testing.
• Provide sufficient technical evidence for QA validation.
• Investigate defects to root cause rather than applying superficial fixes.
• Maintain high code quality through reviews, static analysis, and automated testing.

Cloud, CI/CD & Observability

• Work effectively in cloud-native engineering environments.
• Experience with AWS or comparable major cloud platforms.
• Work with Docker and containerized services.
• Experience with Kubernetes is strongly preferred.
• Participate in CI/CD pipelines and automated deployments.
• Implement structured logging, metrics, tracing, and health checks.
• Diagnose production failures using logs and distributed traces.
• Support monitoring and alerting for backend services.

Required Experience

Applicants must have:

• Minimum 6 years of professional backend software engineering experience.
• Strong experience building production SaaS or enterprise backend systems.
• Strong experience with at least one modern backend language/framework.
• Strong REST API design and development experience.
• Production experience with PostgreSQL.
• Experience designing secure authentication and authorization.
• Experience building multi-user or multi-tenant systems.
• Strong understanding of distributed-system fundamentals.
• Experience with asynchronous processing and/or event-driven architecture.
• Experience integrating external APIs and services.
• Hands-on production experience integrating AI/LLM capabilities.
• Experience with cloud infrastructure.
• Experience with Git and CI/CD workflows.
• Strong automated testing practices.
• Strong debugging and production incident investigation skills.

Strongly Preferred

Preference will be given to candidates with experience in several of the following:

• B2B SaaS platforms
• Enterprise software
• Multi-tenant architecture
• AI-enabled SaaS products
• OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure OpenAI, or comparable AI platforms
• AI tool/function calling
• Structured LLM outputs
• RAG architectures
• Vector databases or semantic retrieval
• AI safety and guardrails
• PostgreSQL Row-Level Security
• Microservices
• Event-driven architecture
• Message queues
• Redis
• Kubernetes
• AWS
• Infrastructure as Code
• OpenAPI/Swagger
• OAuth 2.0/OIDC
• Enterprise security or compliance environments
• Distributed tracing and observability

Technical Expectations

Candidates should be prepared to explain and demonstrate:

• A production backend system they personally designed and implemented.
• How they designed tenant isolation and authorization.
• How they handle idempotency and duplicate requests.
• How they handle transactions and concurrency.
• How they design retry and failure-isolation strategies.
• How they investigate a production API failure.
• How they design secure third-party integrations.
• A production AI/LLM integration they personally implemented.
• How they prevent unreliable AI output from directly affecting critical system state.
• How they handle AI provider failures, timeouts, rate limits, and malformed responses.
• How they monitor AI usage, latency, failures, and cost.
• How they would investigate potential cross-tenant data exposure.

Minimum Qualification Screening

Please apply only if you have:

• 6+ years of professional backend engineering experience.
• Significant production API development experience.
• Production PostgreSQL experience.
• Experience with cloud-based systems.
• Strong backend security knowledge.
• Experience with distributed or asynchronous systems.
• Hands-on production AI/LLM integration experience.

This role is not suitable for candidates whose experience is primarily frontend development, WordPress/CMS development, basic CRUD applications, low-code development, tutorials, or prototype-only AI integrations.

What We Are Looking For

We are looking for an engineer who can independently take a complex backend requirement, challenge weaknesses in the proposed approach, design the technical solution, implement it correctly, test it thoroughly, and prove that it works in a production-like environment.

The successful candidate should be comfortable working in an engineering environment where security, data isolation, reliability, traceability, and technical evidence are treated as part of completion, not optional follow-up work.

You should be capable of explaining not only what you built, but why it was designed that way, how it fails, how it is secured, and how you proved it works.

Interview Process

Shortlisted candidates should expect a rigorous technical interview and practical assessment.

Candidates may be asked to share their screen and walk through appropriate non-confidential examples of previous backend systems, API designs, architecture, code, AI integrations, testing, or other technical evidence.

Candidates must clearly distinguish between systems they personally designed and implemented and work completed by other members of their team.

Pay: ₦1,000,000.00 - ₦1,300,000.00 per month

Application Question(s):

• List your full tech stack
• whats your availability

Education:

• Undergraduate (Required)

Experience:

• BACKEND ENGINEER: 6 years (Required)

Work Location: Remote