Software Engineer with Applied AI Experience

Tkxel; Riyadh; On-site; SAR 250,000 - 420,000; Full time

Job summary

Tkxel in Riyadh invites Software Engineers with Applied AI experience to design, build, and deploy agentic workflows powered by Large Language Models. You will own production-grade AI agents that reason, plan and act across tools, APIs and enterprise data sources.

You will collaborate with enterprise customers in finance, healthcare and telecommunications, deliver measurable business value, ensure reliability and observability from day one, and travel up to 20% to work on-site with partners.

Qualifications

• Hands-on experience building production-grade software in Python.
• Built and deployed high-performance RAG and agentic apps using patterns like ReAct.
• Familiar with LLM stacks, including vector databases and orchestration frameworks.
• Ability to measure agent accuracy, safety, and latency with robust tests.

Responsibilities

• Lead design and delivery of LLM-powered agents across tools and APIs.
• Own end-to-end use-case scoping from concept to production.
• Collaborate with enterprise customers to translate needs into concrete specs.
• Ensure reliability, observability, and auditable AI workflows.

Skills

Python

ReAct

Plan-and-Execute

LLM integration

Evaluation frameworks

Enterprise scale

Tools

Vector databases

Orchestration frameworks

Job description

This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications As a bridge between our core North product and our clients engineering teams you'll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance healthcare and telecommunications We re looking for Software Engineers with Applied AI experience who can own the design build and deployment of agentic workflows powered by Large Language Models LLMs from early prototypes to production-grade AI agents to deliver concrete business value in enterprise workflows You'll work closely with customers on real-world business problems often building first-of-their-kind agent workflows that integrate LLMs with tools APIs and data sources While our pace is startup-fast the bar is enterprise-high agents must be reliable observable safe and auditable from day one Work closely with our enterprise customers to translate high-value ambiguous business problems into well-framed agentic workflows with clear success criteria and evaluation methodologiesLead the design build and delivery of LLM-powered agents that reason plan and act across tools APIs and sensitive enterprise data sources with enterprise-grade reliability and performanceBuild and ship features for North our AI workspace platform working across the full product lifecycle from conceptualization through productionTake ownership of scoping and shaping use cases end-to-end flexing into whatever technical area the problem demands including frontend to drive the most effective solutionContribute to shared frameworks and patterns that enable consistent high-quality delivery across customers and teamsDrive clarity in ambiguous situations build alignment and raise engineering quality across the organizationTravel up to 20 to work on-site with customers and partners

Requirements

You have hands-on experience building production-grade software in Python; you write clean, testable, observable, scalable codeYou've built and deployed highly performant RAG and agentic applications, including agents that plan and execute multi-step tasks using patterns like ReAct or Plan-and-ExecuteYou're deeply familiar with the LLM stack: frontier models, vector databases, and orchestration frameworksYou have a proven ability to build robust evaluation frameworks, moving well beyond trial and error, to measure agent accuracy, safety, and latencyYou're experienced working directly with customers and can lead technical discussions with enterprise stakeholders, translating ambiguous business needs into concrete technical specsYou have experience owning the full scope of a use case end-to-endYou thrive in fast-paced and ambiguous environments and can execute well even when priorities are shifting

It's a bonus if you have:

• Experience setting architectural standards for AI and agentic systems across distributed teams
• Experience flexing into unfamiliar technical areas, such as frontend, when the problem calls for it
• Exposure to regulated or sensitive industry environments (finance, healthcare, telecoms)
• Experience with enterprise security, compliance, or auditability requirements for AI systems