BE ENGINEER

Senior Backend Engineer – Enterprise SaaS, AI & IntegrationsAbout the Role

We are looking for a Senior Backend Engineer who can think beyond tickets and endpoints.

This role is for an engineer who understands how large SaaS platforms actually work: multi-tenancy, distributed systems, API architecture, third-party integrations, asynchronous processing, AI/ML service integration, permissions, billing, auditability, observability, security, data isolation, and production reliability.

We are specifically looking for someone who can understand an existing architecture, challenge weak technical decisions, design solutions before coding, and take features from requirements through production.

This is not a role for an engineer who requires every implementation decision to be made for them.

What You Will Be Responsible For

You will design, build, integrate, test, document, and maintain backend services supporting a large multi-tenant SaaS platform.

Your responsibilities will include:

• Design and develop secure, scalable backend services and APIs for an enterprise SaaS environment.
• Build and maintain multi-tenant architecture with strong tenant isolation across data, permissions, configuration, workflows, usage, and integrations.
• Design services that can support multiple interconnected modules without creating unnecessary dependencies or monolithic bottlenecks.
• Build REST APIs and, where appropriate, event-driven or asynchronous services.
• Own integrations with external platforms across areas such as payments, communications, CRM, productivity, identity, marketing, analytics, storage, and business operations.
• Integrate AI/ML services into production workflows rather than treating AI as a standalone API call.
• Build backend orchestration for AI-powered workflows, including context retrieval, permissions, structured outputs, validation, retries, fallbacks, usage controls, and auditability.
• Work closely with AI/ML engineers to expose models and AI services safely to application workflows.
• Design webhook ingestion and outbound webhook systems with signature verification, idempotency, retry handling, event persistence, and failure recovery.
• Build reliable asynchronous workflows using queues, workers, schedulers, events, or message brokers where appropriate.
• Implement idempotency, concurrency controls, transactional integrity, dead-letter handling, retry strategies, and graceful failure recovery.
• Develop role-based and permission-based access controls suitable for organizations containing multiple users, departments, locations, and administrative levels.
• Support authentication, authorization, SSO and enterprise identity requirements.
• Build backend capabilities for subscriptions, plans, entitlements, usage limits, metering, billing events, upgrades, downgrades, and feature access.
• Design systems capable of supporting multiple countries, currencies, languages, time zones, regulatory requirements, and data-handling rules.
• Maintain comprehensive audit trails for security-sensitive and business-critical actions.
• Implement secure handling of credentials, secrets, tokens, personally identifiable information, and integration credentials.
• Design database schemas and data-access patterns that remain performant as tenant and transaction volumes grow.
• Identify and resolve N+1 queries, inefficient database operations, race conditions, locking issues, memory problems, and performance bottlenecks.
• Implement caching strategically without compromising tenant isolation or data consistency.
• Participate in architecture decisions involving service boundaries, databases, queues, caching, storage, APIs, and integration patterns.
• Write automated unit, integration, contract, and end-to-end backend tests.
• Maintain accurate API documentation using OpenAPI/Swagger or equivalent API-contract tooling.
• Ensure API contracts remain synchronized with implementation and are usable by frontend, mobile, QA, AI/ML, and integration teams.
• Review pull requests critically for architecture, security, performance, maintainability, test coverage, and regression risk—not simply whether the code runs.
• Diagnose production issues using logs, metrics, traces, monitoring, and application telemetry.
• Contribute to CI/CD pipelines, quality gates, deployment processes, rollback strategies, and production-readiness reviews.
• Work closely with frontend, DevOps, AI/ML, QA, security, product, and project teams to deliver complete features.
• Translate product requirements, user stories, workflow diagrams, and technical specifications into reliable backend implementations.
• Identify missing requirements or dangerous assumptions before development, rather than inventing business logic during implementation.

What We Are Looking For

You should have strong professional backend engineering experience building production SaaS systems, preferably platforms serving multiple organizations or enterprise customers.

You should be comfortable demonstrating experience with:

• Strong proficiency in at least one production backend ecosystem such as Node.js/TypeScript, Python, Java, Go, C#/.NET, or an equivalent modern backend stack.
• Designing and maintaining production REST APIs.
• OpenAPI/Swagger or comparable API specification and contract-management tooling.
• Relational databases such as PostgreSQL or MySQL.
• Database modeling, indexing, query optimization, transactions, migrations, and concurrency.
• Redis or comparable caching/state-management technologies.
• Queues, event buses, workers, or messaging technologies.
• Event-driven and asynchronous system design.
• Multi-tenant SaaS architecture.
• Authentication and authorization.
• RBAC and/or more granular permission models.
• OAuth 2.0, JWT, API keys, webhooks, and third-party authentication flows.
• External API and SaaS integrations.
• Cloud infrastructure such as AWS, Azure, or GCP.
• Containers and Docker.
• Git-based engineering workflows and disciplined pull-request practices.
• CI/CD and automated quality controls.
• Logging, monitoring, tracing, and production debugging.
• Secure software-development practices.

AI/ML Integration Experience

We are particularly interested in backend engineers who have implemented AI capabilities inside real production products.

You do not need to be an AI researcher.

However, you should understand the engineering required to integrate AI/ML systems reliably into SaaS applications.

Relevant experience may include:

• LLM/AI API integration.
• Model-service integration.
• RAG or retrieval-based systems.
• Vector databases or semantic retrieval.
• Tool/function calling.
• Structured model outputs.
• AI workflow orchestration.
• Context and conversation management.
• Prompt/version management.
• AI usage metering.
• Rate limiting and cost controls.
• Model-provider abstraction.
• Fallback and retry strategies.
• Human approval workflows.
• AI output validation and guardrails.
• Tenant-aware AI data access.
• Audit logging for AI-driven actions.

Simply having called an LLM API from a demo application will not be considered substantial AI integration experience.

Integration Engineering Is a Major Part of This Role

Candidates should be comfortable working with third-party systems where documentation is incomplete, authentication expires, APIs change, rate limits exist, and failures must be handled safely.

You should understand how to design integrations involving concepts such as:

OAuth → authorization → token exchange → secure token storage → refresh → API execution → webhook/event processing → retries → reconciliation → monitoring → revocation.

Experience integrating platforms in areas such as payments, communications, telephony, email, messaging, CRM, accounting, identity, productivity, cloud storage, marketing, analytics, or social platforms is highly valuable.

Security & Enterprise Readiness

Security is part of backend engineering here—not something delegated entirely to another team.

You should understand practical implementation of:

• Tenant isolation
• Least-privilege access
• Authentication and authorization boundaries
• Encryption in transit and at rest
• Secret management
• Secure API design
• Input validation
• Rate limiting
• OWASP risks
• Audit logging
• Data retention/deletion
• Secure webhook processing
• Sensitive-data handling
• Dependency security
• Production access controls

Experience working in environments influenced by frameworks or requirements such as SOC 2, ISO 27001, GDPR, HIPAA, PCI DSS or similar standards is an advantage.

What Will Make You Stand Out

You will stand out if you can show that you have personally:

• Designed backend architecture for a multi-tenant SaaS product.
• Taken complex features from architecture through production.
• Built substantial third-party integrations.
• Designed systems that remained reliable when external providers failed.
• Integrated AI/ML functionality into production applications.
• Built event-driven or asynchronous architectures.
• Solved difficult scaling, concurrency, or data-consistency problems.
• Designed granular authorization and tenant isolation.
• Worked on enterprise billing, entitlements, metering, or subscription systems.
• Investigated and resolved serious production incidents.
• Improved poorly designed existing systems instead of simply rewriting everything.
• Worked effectively across frontend, AI/ML, DevOps, QA, security, and product teams.

What We Do Not Want

This role is unlikely to be a fit if your experience is primarily:

• Building basic CRUD applications.
• Creating simple APIs from predefined tickets.
• Copying integration examples from vendor documentation without understanding failure scenarios.
• Building prototypes without production ownership.
• Calling an AI API and describing that as AI architecture.
• Coding without automated testing or API documentation.
• Depending on another engineer to make every architectural decision.
• Merging code simply because it compiles or passes a superficial review.
• Ignoring security, observability, scalability, or failure recovery until after deployment.

Ideal Candidate

The right engineer can look at a complex product requirement and think:

What are the domain boundaries? What data belongs where? Who is allowed to access it? What happens asynchronously? What happens if this provider fails? How do we prevent duplicates? How do we recover? How do we observe it? How does this work for thousands of tenants? How do we test it? How do we document the contract? How do we deploy it safely?

If that is naturally how you approach backend engineering, we would like to hear from you.

Application Requirement

Please include examples of production systems you personally helped design or build, specifically identifying your contribution.

Where applicable, describe:

• A multi-tenant SaaS architecture you worked on.
• A complex third-party integration you implemented.
• An AI/ML capability you integrated into a production application.
• A difficult backend reliability, scaling, security, or data-consistency problem you solved.

Generic applications that do not demonstrate relevant backend engineering experience may not progress to the technical interview.

Pay: ₦1,000,000.00 - ₦1,700,000.00 per month

Application Question(s):

• How many years of professional backend engineering experience do you have?

• How many years of experience do you have building production SaaS or enterprise software?

• Have you personally built or maintained multi-tenant SaaS backend systems?

• Do you have hands-on experience integrating third-party APIs, webhooks, OAuth, payment systems, or other external platforms into production applications?

• Do you have hands-on experience integrating AI/ML or LLM capabilities into production applications?

• Are you experienced with API design/documentation (OpenAPI/Swagger or equivalent), databases, queues/background jobs, authentication/authorization, automated testing, and cloud-based production systems?

• What is your expected monthly salary for this full-time position? Please provide the amount and currency.

Work Location: In person