ZigZag is looking for a Fullstack AI Engineer to join their team.
The position is remote and operates on a dayshift schedule.
The candidate should have proficiency in at least one programming language such as Python, C#, JavaScript, Kotlin, Java, or Go.
Experience with Generative AI tools like LangGraph, CrewAI, Hugging Face, and OpenAI APIs is required.
The role involves building and optimizing systems for performance, scalability, and reliability.
A solid understanding of machine learning fundamentals, including training, evaluation, and deployment, is necessary.
The candidate should be familiar with LLM-specific challenges such as prompt engineering, latency, cost optimization, hallucinations, and evaluation.
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 like Prometheus, Grafana, and Datadog, is required.
The candidate should have experience in building distributed systems.
Knowledge and hands-on experience with multiple datastores, both SQL and NoSQL, is necessary.
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.
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.
The candidate must have experience in building and optimizing systems for performance, scalability, and reliability.
A solid understanding of machine learning fundamentals, including training, evaluation, and deployment, is essential.
Familiarity with LLM-specific challenges, such as prompt engineering, latency, cost optimization, hallucinations, and evaluation, is required.
Experience with cloud platforms like AWS, GCP, or Azure and infrastructure-as-code tools like Terraform is necessary.
Hands-on experience with DevOps and infrastructure tooling, including CI/CD, Docker, Kubernetes, and observability tools like Prometheus, Grafana, and Datadog, is required.
The candidate should have experience in building distributed systems.
Knowledge and hands-on experience with multiple datastores, both SQL and NoSQL, is necessary.
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.
The role operates on a dayshift schedule, allowing for a balanced work-life environment.
The opportunity to work with cutting-edge AI technologies and tools is provided.
The candidate will be part of a dynamic team focused on innovation in AI Engineering.
There is potential for professional growth and development within the company.
