AI Systems Engineer (Agentic Development)

About us:Soar is a global fintech startup that specializes in financing and investment. Currently headquartered in Saudi Arabia, Soar is growing throughout the region with a mission to help people achieve their financial goals with innovative financial and property investment solutions and tools through its multi-purpose platform, designed to offer a simple and seamless user experience. Role Summary:This role is for engineers who operate at a higher abstraction level. You will design, manage, and optimize AI agents that generate code, workflows, and business logic. Your responsibility is to ensure outputs are correct, scalable, and aligned with business goals.You are expected to:Reduce development time through AIImprove output quality through validation and iterationContinuously refine agent performance Key Responsibilities:Design and manage agent-based development workflowsOversee AI-generated code: validate, test, refactor, and productionizeBuild systems to evaluate agent output quality and reliabilityFine-tune prompts, tools, and pipelines to improve outcomesIntegrate AI agents into the software development lifecycle (SDLC)Translate business problems (mortgage, real estate workflows) into AI-driven solutionsEstablish best practices for multi-agent collaboration and orchestrationMonitor performance, cost, and accuracy of AI systemsWork across product and business teams to identify automation opportunities Requirements Hands-on experience with LLM-based tools and workflows (e.g., Anthropic Claude or similar)Experience building or managing AI-assisted or agent-driven systemsStrong understanding of modern SDLC with AI accelerationExperience with Google Cloud Platform (GCP) or similar cloud environmentsAbility to review and validate generated code across multiple languagesExperience with prompt engineering, evaluation loops, and model tuningStrong system thinking: can design workflows, not just write functions Preferred Experience Experience with multi-agent systems and orchestration frameworksFamiliarity with real estate or mortgage workflows (not required but valuable)Experience with vector databases, RAG pipelines, or knowledge systemsExposure to tools like "antigravity"-style AI workflows or similar emerging platforms What Success Looks Like Development cycles reduced significantly through AI leverageHigh-quality outputs from agents with minimal reworkClear frameworks for agent validation and monitoringEngineers spend more time on problem-solving and innovation, less on manual coding. Benefits Build an AI-first company from the ground upWork on real-world, high-impact problems in real estate and mortgageOperate in a fast, experimental, innovation-driven environmentShape how engineering is done—not just what is built