GenAI, Sr. Data Engineer (Remote - US)

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a GenAI, Sr. Data Engineer in the United States.

As a Senior Data Engineer specializing in Generative AI orchestration, you will be responsible for designing, integrating, and managing large-scale AI workflows that connect multiple models, APIs, and services. You will play a key role in enabling the automation and scalability of advanced AI-driven systems while collaborating with data scientists, engineers, and business teams. This role offers the opportunity to shape next-generation AI infrastructure, ensuring seamless performance, reliability, and innovation. You’ll thrive in a dynamic, forward-thinking environment that values creativity, collaboration, and technical excellence.

Accountabilities:

• Design and implement orchestration pipelines that integrate multiple Generative AI models, APIs, and tools into cohesive end-to-end workflows.
• Collaborate closely with data scientists, engineers, and business stakeholders to define AI use cases and translate them into automated solutions.
• Optimize system performance, scalability, and reliability through effective orchestration and monitoring strategies.
• Integrate AI orchestration platforms with cloud infrastructures and enterprise systems.
• Establish and document best practices for versioning, lifecycle management, and performance tracking of AI systems.
• Continuously research and implement improvements in orchestration frameworks, LLM performance, and automation tools.
• Maintain detailed documentation of technical architectures, orchestration processes, and deployment standards for knowledge sharing.

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field (or equivalent experience).
• 3+ years of experience in AI/ML engineering, data engineering, or workflow orchestration (experience with GenAI/LLM orchestration is a strong plus).
• Proficiency with orchestration tools such as Airflow, Prefect, LangChain, Dagster, or Kubeflow.
• Strong programming skills in Python for building, automating, and integrating AI workflows.
• Hands-on experience with cloud environments (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
• Understanding of Generative AI model deployment, including LLMs and diffusion models.
• Strong analytical and problem-solving abilities with a focus on performance optimization.
• Excellent communication skills and a collaborative mindset to work effectively across technical and non-technical teams.
• Ability to balance innovation with reliability, security, and compliance standards.