Skills
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Go
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ML
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CI/CD
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AWS
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Docker
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Kubernetes
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Backend Development ꞏ 5y
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Agentic Architectures
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AI Workflows
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Algorithmic Systems
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Cloud-Native Environments
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LLMs
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Model Deployment
- Design, build, and maintain backend services and infrastructure that power our agent and AI systems.
- Develop and deploy algorithms and models, integrating them seamlessly into production environments.
- Collaborate closely with the AI research, product, and platform teams to design custom and proprietary solutions for our agents.
- Work on end-to-end system architecture - from data pipelines and model serving to inference and optimization.
- Contribute to the development of tools and frameworks for deploying, monitoring, and evaluating LLM-powered applications.
- Drive innovation by improving agentic AI systems, advancing capabilities such as reasoning, autonomy, and coordination.
- Experiment with and apply context engineering techniques to enhance LLM understanding, consistency, and performance in dynamic environments.
- Bring research ideas into production reality through rapid prototyping and iteration.
Requirements:
- 5–8+ years of experience in software engineering, with a focus on backend development.
- Proven experience working with machine learning or algorithmic systems — ideally deploying models or integrating AI workflows into backend services.
- Hands-on experience with LLMs and agentic architectures (e.g., building or orchestrating autonomous or semi-autonomous agents).
- Experience with cloud-native environments (AWS, Docker, Kubernetes) and CI/CD pipelines.
- Experience with Go is a strong advantage.
- Track record of building scalable, reliable systems in fast-paced environments.
- Strong problem-solving skills, creativity, and a deep curiosity about applying AI to real-world products.
- Great communicator and collaborator who thrives in cross-functional R&D teams.
Wonderful.ai
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