SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Toters is an on-demand e-commerce and delivery platform operating in the Middle East, focused on enabling customers to get anything in their city with high convenience. The company is technology-driven, with product and engineering teams building customer-facing experiences and internal systems for speed and cost efficiency.
You will join as a Senior AI Platform Engineer, sitting at the intersection of backend engineering, AI engineering, platform engineering, and developer enablement. This is a forward-deployed engineer (FDE) style role: highly hands-on, comfortable across technical areas, able to understand ambiguous problems quickly, and capable of turning emerging AI capabilities into practical solutions.
Key responsibilities:
- Design and build backend systems and services powered by AI, integrating AI capabilities into production-grade products and internal platforms.
- Own the AI engineering lifecycle from experimentation and prototyping through deployment, observability, evaluation, and continuous improvement.
- Build and evolve AI-enabled developer and engineering platforms that improve productivity and accelerate software delivery.
- Lead adoption of AI tools and workflows across engineering, helping teams identify high-value use cases and scale solutions.
- Establish engineering standards and best practices around AI-powered development, agents, evaluation, observability, reliability, and productionization.
- Explore and implement emerging agentic engineering patterns, including agent-to-agent protocols, agent SDKs, tool calling, orchestration, and autonomous workflows.
- Build systems leveraging knowledge bases, knowledge graphs, retrieval, and contextual data to make AI applications more useful and reliable.
- Work closely with Backend, Platform, ML, Product, and Engineering leadership to identify opportunities where AI can improve products and internal workflows.
- Prototype rapidly, validate ideas, and move successful experiments into reliable production systems.
- Develop reusable frameworks, libraries, and services enabling other engineers to build AI-powered applications.
- Define and improve AI observability and evaluation practices, including monitoring quality, performance, reliability, cost, and model behavior.
- Stay current with rapidly evolving AI technologies and translate them into practical engineering solutions.
Requirements:
- 6+ years of software engineering experience with strong background in Backend Engineering, Platform Engineering, or similar technical discipline.
- Strong experience building production-grade backend systems, preferably at significant scale.
- Strong programming skills in one or more backend languages: Go, Java, or PHP.
- Hands-on experience building or integrating AI-powered systems and applications.
- Strong understanding of the AI application lifecycle, from experimentation to production deployment and monitoring.
- Experience with AI developer tools, LLMs, agents, agent SDKs, and AI-assisted software engineering workflows.
- Demonstrated experience leading AI adoption or enablement across an engineering team or organization.
- Ability to understand emerging AI technologies and distinguish between what is genuinely useful in production and what is experimental.
- Strong understanding of software architecture, distributed systems, APIs, and backend infrastructure.
- Experience with observability, reliability, monitoring, and production operations for complex systems.
- Strong problem-solving skills and ability to work effectively in ambiguous, fast-moving environments.
- Builder mindset: comfortable going from "we should try this" → prototype → production.
Nice to have:
- Experience with AWS or other major cloud platforms.
- Experience with Platform Engineering or Developer Experience / Developer Enablement.
- Experience with MLOps or ML/AI infrastructure.
- Experience building AI agents and agentic workflows.
- Experience with Agent SDKs, agent-to-agent communication protocols, and orchestration frameworks.
- Experience with knowledge graphs, knowledge bases, RAG, or other approaches for grounding AI systems in company/domain knowledge.
- Experience building AI-powered developer tools or internal engineering platforms.
- Previous experience in FDE, Solutions Engineer, Developer Experience, AI Platform, or similar highly cross-functional engineering role.
- Experience working with modern AI coding and development tools such as Claude or similar AI development platforms.
