Jobs at Shyftlabs

• Own the end-to-end product strategy, vision, roadmap, and execution for one or more technical product lines.
• Lead products through the full lifecycle, from discovery and problem definition through development, launch, adoption, and continuous improvement.

• Own the roadmap for one or more data and AI product lines — you set priorities, you defend the trade-offs, and you're accountable for the results.
• Run discovery directly with enterprise clients and internal stakeholders to identify high-value problems worth solving, and separate them from the noise.

• Lead the architecture, design, and implementation of enterprise-scale data platforms from project inception through production deployment.
• Own technical delivery across multiple client engagements while ensuring high-quality engineering standards.

• Personally design, build, and operate the cloud infrastructure, CI/CD pipelines, and underlying platform that our production, QA, and development environments run on.
• Write the automation, IaC, and tooling yourself, including Terraform modules, deployment scripts, and glue code that removes manual work for the whole team.

• Build and improve agent orchestration and multi-agent workflows.
• Develop agentic applications for enterprise use cases using Continuum.

• Own the end-to-end lifecycle of analytical data products, from discovery and roadmap planning through delivery, adoption, and continuous improvement.
• Define product vision and priorities aligned with client business objectives and organizational strategy.

• Responsible for the development, optimization and delivery of cloud computing solutions, hosted services and underlying software infrastructure to optimize service delivery across production, QA and development environments through the development lifecycle
• Supports and troubleshoots scalability, high availability, performance, monitoring, backup and ...

Position Overview:

We at ShyftLabs are seeking a highly motivated and curious Software Developer to join our growing engineering team. This role is ideal for students who are excited to learn, eager to build, and passionate about working on real-world challenges in a fast-paced, agile environment.

• Assist in building and integrating AI-powered features into backend applications and workflows
• Work with LLM APIs, machine learning models, and automation pipelines to support intelligent product experiences

• Architect and implement AI-powered features end-to-end, from model integration and prompt engineering to deployment, monitoring, and iteration
• Integrate LLM APIs, ML models, and intelligent automation pipelines into scalable, production-grade backend systems

• Design and development of scalable, service-based architectures (front-end and back-end), while remaining hands-on in coding and delivery
• Architect and implement system integrations across internal services and third-party platforms (REST, GraphQL, event streams, webhooks, ETL pipelines)

• Design, build, and maintain scalable and reliable batch and real-time ETL/ELT data pipelines using cloud services such as GCP Dataflow, Cloud Functions, Pub/Sub, and Cloud Composer.
• Architect and implement robust data infrastructure capable of handling high-volume data ingestion and processing.