Senior Backend & Platform Engineer, Forward Deployed

About OryonTech

OryonTech develops Agent as a Service, a WhatsApp-first platform that enables businesses to manage customer interactions, orders, bookings, payments, and operational workflows. The platform combines conversational AI with authoritative backend systems and human oversight.

Our engineering priorities are reliable execution, secure multi-tenant operation, transaction correctness, and measurable value for the businesses using the product.

Position overview

We are seeking a senior backend engineer to take technical ownership of the business systems behind OryonTech and lead capabilities from customer discovery through production operation.

This is not a ticket-only backend role. You will work close to merchants and internal teams, understand the workflow that needs to succeed, shape the technical approach, implement critical services, and remain accountable through rollout and production verification.

You will own and evolve APIs, data models, background jobs, event-driven workflows, billing and payment flows, integrations, and other backend primitives that must remain correct even when requests are retried, external systems fail, or AI agents initiate an action.

Working with Applied AI, frontend, infrastructure, product, and GTM colleagues, you will turn recurring deployment needs into reusable platform capabilities instead of one-off customer code.

AI-assisted engineering (required)

You must actively use company-approved AI coding assistants and agentic development tools as part of your daily engineering workflow to build and improve production software efficiently. This is a core requirement, not an optional advantage, and applies to your own development process, not only to building AI product features.

• Use AI tools for research, planning, prototyping, implementation, refactoring, testing, debugging, documentation, and production diagnosis when appropriate to the task.
• Supply relevant codebase context, API contracts, constraints, failure cases, and acceptance criteria; iterate deliberately rather than accepting the first generated answer.
• Understand, review, test, and explain every change you ship. AI output does not replace engineering judgment, code review, security checks, or deployment approval.
• Protect credentials, personal information, customer data, and proprietary code. Use only approved tools and data-handling settings, keep access least-privileged, and never give AI tools uncontrolled production access.
• Build reusable prompts, instructions, tests, and automation that reduce repetitive work. Demonstrate efficiency through delivery time, reduced rework, and reliable outcomes, not lines of generated code; keep tool usage and cost proportionate.
• Use AI tools to accelerate API and integration development, SQL and migration reviews, transactional tests, and production debugging; independently verify idempotency, authorization, tenant isolation, and payment correctness.

During technical screening, be ready to walk through an AI-assisted change, explain what you accepted or rejected, and show how you verified correctness. No additional document or exercise is required with your initial CV email.

Principal responsibilities

Backend architecture and platform development

• Lead the design and evolution of Python/FastAPI services, APIs, data models, background jobs, queues, and event-driven workflows.
• Own backend authority for permissions, pricing, catalog and inventory state, orders, bookings, billing, payments, fulfillment, and other critical business rules.
• Design for transaction correctness using validation, database constraints, idempotency, concurrency control, retries, reconciliation, and explicit failure recovery.
• Develop and maintain integrations with WhatsApp, payment providers, booking systems, email, and other business services.
• Assess existing code and data flows, identify technical debt and scaling constraints, and lead proportionate refactors and migrations with rollback plans.

Customer discovery and forward-deployed delivery

• Lead technical discovery with merchants and internal stakeholders. Translate real business workflows into technical scope, acceptance criteria, dependencies, and implementation plans.
• Own assigned capabilities from discovery and prototyping through implementation, integration, testing, controlled rollout, and post-deployment verification.
• Explain technical constraints and trade-offs in plain language to customer-facing colleagues and, where appropriate, directly to merchants.
• Convert recurring customer needs into configurable platform features, reusable integrations, and documented implementation patterns.

Reliability, security, and production ownership

• Enforce tenant isolation, authorization, safe data access, and secure service-to-service behavior.
• Diagnose and resolve production incidents involving data integrity, integrations, latency, concurrency, retries, and external-provider failures.
• Work with infrastructure engineering on GCP service objectives, monitoring, deployment controls, secrets, recovery, and capacity.
• Maintain useful operational visibility through structured logs, correlation IDs, metrics, alerting, and runbooks.
• Protect backward compatibility and customer operations during API, schema, and service changes.

Engineering leadership

• Lead backend design discussions and code reviews, mentor colleagues, and establish maintainable engineering standards.
• Use approved AI engineering tools deliberately for investigation, implementation, testing, debugging, and documentation while remaining accountable for every delivered change.
• Document material architecture decisions, dependencies, migration plans, and operational procedures.
• Surface risks and trade-offs early and bring a recommended path forward rather than waiting for complete instructions.

Required qualifications

• Demonstrated practical use of AI-assisted engineering tools to deliver tested software, with the ability to independently explain, debug, and maintain the resulting work.
• A substantial record of professional software engineering with demonstrated ownership of customer-facing backend systems in production.
• Advanced Python proficiency and strong experience with FastAPI, Django, Flask, or a comparable backend framework.
• Strong PostgreSQL and SQL capability, including relational modeling, transactions, indexes, constraints, migrations, and data integrity.
• Practical experience with Redis, asynchronous processing, queues/background jobs, APIs, webhooks, and event-driven systems.
• Demonstrated experience designing retry-safe and idempotent transactional flows.
• Experience deploying and operating containerized services on GCP, AWS, or Azure, with working knowledge of CI/CD, secrets management, permissions, monitoring, and incident response.
• Experience integrating third-party APIs where external failures, rate limits, duplicate events, and reconciliation matter.
• Strong debugging ability across application, database, integration, and infrastructure boundaries.
• Experience translating ambiguous business requirements into technical scope and delivering against clear acceptance criteria.
• Evidence of independent judgment, effective code review, technical communication, and knowledge transfer.

Preferred experience

• GCP, including Cloud Run, Cloud SQL, Pub/Sub, Secret Manager, Cloud Storage, and Cloud Logging.
• WhatsApp Business Platform, Meta Cloud API, or Twilio integrations.
• Payment systems such as Paystack, Stripe, or Flutterwave, including webhooks, reconciliation, and settlement flows.
• Booking, commerce, billing, subscription, or other transactional products with strict correctness requirements.
• Multi-tenant SaaS systems, row-level security, audit logging, and usage metering.
• LangGraph, LLM tool calling, or backend integration with AI agents.
• Previous forward-deployed, founding-engineer, or customer-facing implementation experience.

Performance expectations

Success will be assessed against technical and business outcomes:

• Critical backend workflows remain correct through retries, concurrency, provider failures, and recovery.
• Customer deployments reach acceptance with clear evidence and minimal recurring manual intervention.
• Repeated implementation needs become reusable platform capabilities.
• Production failures are diagnosable, recoverable, and less likely to recur.
• Backend architecture, data integrity, and operating cost improve without unnecessary complexity.
• Other engineers can understand, maintain, and safely operate the systems you own.

Specific targets will be established from the current platform baseline and the priorities agreed for the role.