Jobs at Shyftlabs

• 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.

• Own and grow a portfolio of strategic accounts across retail media, commerce media, brand, and agency relationships, driving net revenue retention and expansion.
• Serve as a trusted advisor and strategic partner to key client stakeholders on commerce media strategy, onsite and offsite activation, closed-loop measurement, and AI-driven optimization.

• 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

• Design end-to-end solutions spanning data pipelines, application services, and cloud infrastructure across major public clouds (GCP, AWS, Azure).
• Make architecture decisions on data warehousing (BigQuery, Databricks, Snowflake, ClickHouse), event/streaming layers (Kafka), API design, and cloud networking (DNS, CDN, WAF, identity, load balancing).

• 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

• Own the technical narrative in enterprise deals: Translate ambiguous client challenges into structured problem definitions and solution architectures grounded in real-world constraints such as data availability, infrastructure, and governance. Clearly articulate why proposed solutions will succeed and where alternative approaches fall short.

• 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.

• Innovation & Project Ownership: Drive the end-to-end (E2E) delivery of complex features and innovation projects. You will own the entire lifecycle, including architectural design (iDesign), development, rigorous testing, production deployment, and post-launch hypercare.
• Full Stack Development: Lead the implementation of scalable backend APIs using Python (FastAPI...

• Own the technical vision and architecture for analytics and data platforms, ensuring solutions are scalable, secure, and aligned with enterprise standards.
• Lead the design and implementation of end-to-end data architectures, including data lakes, data warehouses, analytics layers, and ML-ready data pipelines.

• Design and influence the development of service-based systems (both front-end and back-end) with an emphasis on scalable, event-driven architectures.
• Collaborate with the Product team to understand requirements, provide estimates, assess technical complexity, and identify dependencies, risks, and roadblocks.

• Own and drive the end-to-end lifecycle of key technical initiatives across multiple projects.
• Define technical requirements, product roadmaps, and detailed solution specifications.

• Design and implement AI automation pipelines using Python (FastAPI, LangChain, spaCy) or Node.js (LLM API wrappers, task automation frameworks).
• Build and optimize OCR-based data extraction systems for invoices, receipts, and other unstructured documents, integrating semantic search and rule-based classification workflows.

• Transform Carter’s platform from a traditional ad interface into natural conversational workflows.
• Design AI-powered guidance features that help users discover opportunities and optimize performance.