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Senior AI Software Engineer Onsite In Riyadh- Octopus by RTG

Senior AI Software Engineer Onsite In Riyadh- Octopus by RTG

Robusta StudioRiyadh, Riyadh Region, Saudi Arabia
22 منذ أيام
الوصف الوظيفي

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
  • #J-18808-Ljbffr

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