ZigZag is looking for a Fullstack AI Engineer to join their team.
The position is remote and operates on a dayshift schedule.
The ideal candidate should have proficiency in at least one programming language such as Python, C#, JavaScript, Kotlin, Java, or Go.
Candidates should have experience with Generative AI tools, including but not limited to LangGraph, CrewAI, Hugging Face, and OpenAI APIs.
The role requires experience in building and optimizing systems for performance, scalability, and reliability.
A solid understanding of machine learning fundamentals, including training, evaluation, and deployment, is necessary, along with knowledge of LLM-specific challenges like prompt engineering, latency, cost optimization, hallucinations, and evaluation.
Experience with cloud platforms such as AWS, GCP, or Azure, as well as infrastructure-as-code tools like Terraform, is required.
Candidates should be hands-on with DevOps and infrastructure tooling, including CI/CD, Docker, Kubernetes, and observability tools like Prometheus, Grafana, and Datadog.
Experience in building distributed systems is essential.
Knowledge and hands-on experience with multiple datastores, both SQL and NoSQL, are required.
Desired experience includes building agents and workflows, such as autonomous systems or multi-agent architectures.
A passion for AI Engineering is a must.
Fluency in English is required.
Requirements:
Proficiency in at least one programming language, such as Python, C#, JavaScript, Kotlin, Java, or Go, is required.
Experience with Generative AI tools, including LangGraph, CrewAI, Hugging Face, and OpenAI APIs, is necessary.
Candidates must have experience in building and optimizing systems for performance, scalability, and reliability.
A solid understanding of machine learning fundamentals and LLM-specific challenges is required.
Experience with cloud platforms like AWS, GCP, or Azure, and infrastructure-as-code tools such as Terraform is essential.
Hands-on experience with DevOps and infrastructure tooling, including CI/CD, Docker, Kubernetes, and observability tools, is required.
Experience in building distributed systems is necessary.
Knowledge and hands-on experience with multiple datastores, both SQL and NoSQL, are required.
Desired experience includes building agents and workflows, such as autonomous systems or multi-agent architectures.
A passion for AI Engineering is essential.
Fluency in English is required.
Benefits:
The position offers the flexibility of remote work.
Employees will have the opportunity to work in a dynamic and innovative environment focused on AI Engineering.
The role provides the chance to work with cutting-edge technologies and tools in the AI field.
Employees will be part of a team that values passion and expertise in AI Engineering.
