Senior AI Software Engineer Onsite In Riyadh- Octopus by RTG

Overview Senior AI Software Engineer onsite in Riyadh – Octopus by RTG. Octopus by RTG is enabling a key partner organization to grow their tech teams while focusing on AI. We are currently looking for the right pioneers to join the team!

Role Summary A Senior Software Engineer with 6+ years of experience building AI-powered applications. Works under the

Principal Data & AI Delivery Lead

to translate strategy into robust software solutions. Responsible for designing and shipping model-backed features, high-quality APIs, and user-facing services with strong security, reliability, and performance. Experience in public sector or other regulated domains is a plus.

Core Responsibilities

Delivery Execution : Design and implement backend services and APIs that integrate AI capabilities; apply suitable architectural patterns; follow coding standards with peer reviews.

Model Serving & Inference : Package models as services, optimize latency and throughput, and apply safe rollout strategies such as canary releases and A / B testing.

Retrieval & Context : Enable semantic search and assistant features using embeddings, vector search, and prompt orchestration where appropriate.

Client Integration : Define clear API contracts and lightweight SDKs; collaborate with web and mobile teams to deliver end-to-end features.

Security & Privacy : Implement authentication, authorization, encryption at rest and in transit, secrets management, and responsible handling of personal data; align with governance controls.

Observability & Reliability : Instrument services with metrics, logs, and traces; define service objectives and alerts; participate in incident response and post-incident reviews.

Continuous Delivery & Platform Engineering : Use containerization, orchestration, infrastructure as code, and automated pipelines for build, test, and deployment with environment promotion.

Testing : Write unit, integration, contract, and performance tests; mock or stub model endpoints to ensure repeatable test runs.

Documentation & Knowledge Sharing : Produce technical documentation, diagrams, and runbooks; contribute to reusable components, patterns, and templates.

Pilot & Scale Support : Support controlled pilots, gather feedback, harden services for production scale, and hand over cleanly to operations.

Requirements

6+ years in software engineering, including 3+ years building cloud services at scale.

2+ years implementing AI capabilities in production (e.g., large language model features, NLP, computer vision, and recommendation systems).

Experience training and serving machine learning models using industry-standard tools and practices.

Proven integration of foundation models via managed services or self-hosted deployments.

Experience with retrieval-augmented generation (RAG) patterns, vector databases, and embeddings.

Practical use of relational and non-relational datastores, caching, and event streaming or messaging platforms.

Cloud platform experience, containerization and orchestration, and CI / CD with Git-based workflows.

Security-first development practices, identity and access management.

Familiarity with regulated or public sector environments is a plus.

Skills & Competencies

Software Design & Architecture : Clean code, API-first design, modular architectures, and appropriate service boundaries.

AI Product Thinking : Translate model capabilities into reliable user features, set guardrails and fallbacks, monitor quality and safety.

Performance Engineering : Profiling, caching, batching, and concurrency to meet latency and throughput targets.

Quality Mindset : Automated testing, code reviews, static analysis, and continuous improvement.

Delivery Skills : Estimation, task breakdown, and agile ways of working with clear status reporting.

Communication & Collaboration : Clear documentation, close partnership with Product, Security, and QA teams, and mentoring of junior engineers.

Problem-Solving : Structured analysis, prioritization, and proactive risk management.

Education & Credentials

Bachelor's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience).

Relevant certifications are a plus (e.g., cloud provider certifications, container orchestration, applied machine learning).

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Other

Industries

IT Services and IT Consulting

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