Senior / Staff AI Platform Engineer: Agents & AI SDLC

Toters•Geraldine, AL

13d

About The Position

Toters is an on-demand e-commerce and delivery platform that enables customers to get anything in their city with the highest level of convenience. Technology is at the heart of everything we do. Our product and engineering teams work every day to build experiences that make customers’ lives easier while continuously improving internal systems to deliver faster and at the best cost. If you’re excited about working in a high-growth startup environment and want to be part of a team shaping the future of how people shop in the Middle East, we’d love to hear from you. We are looking for a Senior AI Backend Engineer to join Toters and help us build and scale the next generation of AI-powered products and engineering systems. This role sits at the intersection of Backend Engineering, AI Engineering, Platform Engineering, and Developer Enablement. We are looking for someone who not only builds AI-powered systems, but also understands how AI is adopted across an engineering organization and can help teams use AI effectively in their day-to-day development and product delivery. The ideal profile is similar to an Forward Deployed Engineer (FDE): highly hands-on, comfortable working across different technical areas, able to understand ambiguous problems quickly, and capable of turning emerging AI capabilities into practical solutions. You will help define what good looks like for AI engineering at Toters, build reusable foundations, and enable engineering teams to adopt AI tools, agents, and AI-powered development practices.

Requirements

6+ years of experience software engineering, with a strong background in Backend Engineering, Platform Engineering, or a similar technical discipline.
Strong experience building production-grade backend systems, preferably at significant scale.
Strong programming skills in one or more backend languages such as 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 the ability to work effectively in ambiguous, fast-moving environments.
A builder mindset: you are comfortable going from "we should try this" → prototype → production.

Nice To Haves

Experience working 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 an 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.

Responsibilities

Design and build backend systems and services powered by AI, integrating AI capabilities into production-grade products and internal platforms.
Own and contribute to 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 the adoption of AI tools and workflows across engineering, helping teams identify high-value use cases and turn them into scalable 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 that leverage 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 meaningfully improve products and internal workflows.
Prototype rapidly, validate ideas, and move successful experiments into reliable production systems.
Develop reusable frameworks, libraries, and services that allow other engineers to build AI-powered applications without reinventing the foundations.
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 for Toters.