ShyftLabs

Data Scientist

• Analyze large datasets using queries and scripts to extract meaningful insights and identify opportunities for improving complex ML and bidding systems.
• Design and execute simulations to validate hypotheses, quantify efficiency gains, and model system performance.
• Develop robust experiment designs and metric frameworks to deliver unbiased, data-backed insights for product and business decisions.
• Build, train, and deploy ML models into production environments, managing the full lifecycle including versioning, monitoring, and retraining.
• Operationalize ML models at scale, optimizing for performance, reliability, and cost efficiency in real-world production systems.
• Work closely with product, engineering, and data teams to translate business problems into analytical solutions.

Data Engineer

• Collaborate with cross-functional teams to define requirements and deliver reliable solutions.
• Design, develop, and maintain data pipelines and ETL/ELT processes using Python.
• Build and optimize scalable, high-performance data applications.
• Develop and manage real-time streaming pipelines using Pub/Sub or Apache Beam.
• Participate in code reviews, architecture discussions, and continuous improvement initiatives.
• Monitor, troubleshoot, and optimize production data systems for reliability and performance.

• Collaborate with Data Engineers, Analysts, and Product Managers to design and implement end-to-end, cloud-based data solutions.
• Assist in developing and maintaining ETL pipelines using modern data engineering tools and best practices.
• Support the creation of reliable, scalable, and secure data workflows across cloud environments (AWS, GCP, or Azure).
• Contribute to data quality, reliability, and automation initiatives to enhance existing processes.
• Participate in source control, testing, and CI/CD practices to support agile data delivery.
• Engage in team meetings, sprint reviews, and design discussions to gain exposure to the full data lifecycle.

Data Engineering Intern

Data Analyst

• Analyze large and complex datasets to identify key trends, insights and opportunities that influence business decisions.
• Build and maintain impactful dashboards and reports using Looker, Tableau or Power BI.
• Translate business questions into analytical solutions and communicate results in a clear, actionable way.
• Partner with business teams (e.g., Marketing, Merchandising, Data Science) to understand objectives and develop insights that drive performance.
• Create compelling data stories - combining analytics, design and business acumen to explain the “why” behind the numbers.
• Develop advanced SQL queries for data exploration, validation and ad-hoc analysis.
• Maintain a deep understanding of key business KPIs and continuously improve how they are visualized and interpreted.

Senior Data Analyst

• Analyze large and complex datasets using SQL, Python, or R to uncover insights, identify trends, and support data-driven business and product decisions.
• Conduct exploratory data analysis, build models, and run simulations to validate hypotheses and quantify potential outcomes.
• Assist in designing and analyzing experiments to measure performance, determine causality, and generate actionable recommendations.
• Partner with engineers, product managers, and other stakeholders to translate data findings into impactful strategies and solutions.
• Communicate insights effectively through dashboards, reports, and visual presentations that enable clear understanding and decision-making.

Data Science Intern

DevOps Engineer

• spend the bulk of their time designing and implementing given requirements supplied by the product teams
• delivery of digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation

Business Analyst

• Act as a Business Analyst for a data implementation focused on large financial data
• Work with stakeholders to gather, refine, and document business requirements for CRM customization and data integration
• Collaborate with data engineering and application development teams to ensure end-to-end orchestration of business and data workflows
• Conduct data mapping, analysis, and validation across CRM, ERP, and other systems
• Support the key transactional process by understanding data dependencies, integration points, and reporting needs
• Create, refine, and clean up Jira stories to align with project requirements and Agile delivery
• Partner with executives and stakeholders to communicate requirements, progress, and outcomes
• Support API integration efforts to ensure related platforms interact seamlessly with upstream and downstream systems
• Leverage SQL to analyze and validate data, perform transformations, and ensure reporting accuracy
• Participate in workshops, demos, and executive presentations to align business objectives with system functionality
• Ensure project deliverables meet scope, timeline, and quality expectations

Senior Business Analyst

Product Manager

• Define the AI product strategy and roadmap, including monetization models, to accelerate adoption across ShyftLabs’ solutions.
• Conduct market, user, and developer research to identify opportunities and shape product direction.
• Translate strategic business outcomes into actionable Objectives and Key Results (OKRs) to align with company goals.
• Partner with UX, engineering, and data science teams to design, prototype, and launch AI-driven features.
• Lead cross-functional initiatives to develop new platform capabilities and scale successful use cases across products.
• Define and monitor Key Performance Indicators (KPIs) to track adoption, performance, and impact of AI features.
• Actively experiment with LLMs, agent-based workflows, and orchestration tools like N8N to identify innovative solutions.
• Communicate plans, progress, and outcomes transparently with leadership and stakeholders.
• Stay current on emerging technologies such as LLMOps, Model Context Protocol, and multi-agent AI workflows to inform product decisions.

Product Manager, AI

Full-stack Engineer

• Build and enhance Amazon Connect contact flows for calls and chat with Lambda, Lex, and third-party integrations
• Develop backend services in Python or Node.js
• Develop agent/customer interfaces in React (JavaScript)
• Integrate with AWS services (Lambda, API Gateway, Lex, DynamoDB, S3, IAM, CloudWatch, CloudFormation, Q in Connect, Kinesis, Secrets Manager, CloudFront)
• Contribute to Infrastructure-as-Code deployments using Terraform and GitLab CI/CD pipelines
• Create and execute manual test cases for Connect flows, APIs, and front-end applications
• Perform integration testing across AWS services, Connect flows, and external systems (e.g., CRM)
• Track, document, and resolve issues while collaborating with development and DevOps teams
• Ensure test coverage for security, scalability, and cost efficiency
• Provide L2/L3 support for Amazon Connect flows, APIs, and integrated applications
• Monitor logs, metrics, and alerts (CloudWatch, Kinesis, etc.) to ensure system stability and performance
• Troubleshoot and resolve production issues in collaboration with engineering and operations teams
• Document incidents, fixes, and best practices to improve knowledge sharing and reusability
• Participate in on-call rotations or scheduled support activities as required

Full Stack Developer

AI Engineer

• Research, design, and develop AI-powered applications and solutions that address complex business challenges.
• Implement and integrate AI models into scalable production environments.
• Collaborate with cross-functional teams to deliver end-to-end AI solutions.
• Optimize AI implementations for performance, reliability, and cost efficiency.
• Apply engineering best practices to ensure AI systems meet quality standards and can scale.
• Stay current with the latest AI tools and frameworks to propose innovative solutions.
• Document technical processes and implementations to improve knowledge sharing.

Senior AI Engineer

Product Designer

• Lead design efforts for the Carter platform, focusing on dashboards, campaign management, audience tools, reporting interfaces, and workflow optimization
• Collaborate with cross-functional teams to translate business goals and complex use cases into simple, intuitive user journeys
• Create user flows, wireframes, high-fidelity UI designs, and interactive prototypes that demystify data-driven features and ML-powered insights
• Ensure Carter’s UI adheres to best-in-class standards for accessibility, consistency, and responsiveness across devices
• Maintain and evolve the Carter design system, component library, and brand guidelines
• Communicate design concepts, rationale, and user research findings persuasively to engineering and leadership, fostering alignment throughout the product lifecycle
• Stay informed on design trends, the adtech ecosystem, and enterprise SaaS usability best practices to ensure Carter delivers value and differentiation

Senior UI/UX Designer

Frontend Engineer

• Develop and maintain rich, responsive web applications using React.js and Next.js.
• Build reusable UI components and ensure consistent design implementation across products.
• Optimize applications for performance, accessibility, SEO, and cross-browser compatibility.
• Integrate with backend APIs and work on real-time, CMS-driven content delivery.
• Implement state management (Redux, Zustand, Recoil, or similar) for scalable apps.
• Collaborate with backend engineers on API contracts and micro-frontend integration.
• Work with GitOps-driven CI/CD pipelines, Dockerized builds, and Kubernetes deployments.
• Ensure secure and efficient handling of user data in multi-tenant SaaS environments.

Frontend Software Engineer

QA Engineer

• Ensure the quality and reliability of cutting-edge AI applications serving Fortune 500 companies
• Design and execute comprehensive test strategies for AI applications, including model performance, accuracy, and reliability testing
• Develop automated test frameworks for enterprise integrations, APIs, and real-time data processing systems
• Perform end-to-end testing of agentic AI workflows and complex multi-system integrations
• Collaborate with engineering teams to implement continuous testing practices and quality gates
• Test cloud-agnostic deployments across AWS, Azure, and GCP environments
• Conduct performance testing for high-throughput enterprise workloads and scalability requirements
• Work with Product Managers and Technical Leads to define acceptance criteria and testing requirements

• Act as the first point of contact for data issues in the Master Data Management (MDM) system.
• Investigate and resolve data-related issues, such as duplicate data or missing records, ensuring timely and accurate updates.
• Coordinate with the Product Manager, QA Lead, and Technology Lead to prioritize and address tickets effectively.
• Work on Data related issues, ensuring compliance with regulations.
• Build and optimize data models to ensure efficient storage and query performance, including work with Snowflake tables.
• Write complex SQL queries for data manipulation and retrieval.
• Collaborate with other teams to diagnose and fix more complex issues that may require code changes or system updates.
• Utilize AWS resources like CloudWatch, Lambda, SQS, and Kinesis Streams for data storage, transformation, and analysis.
• Update and maintain the knowledge base to document common issues and their solutions.
• Monitor system logs and alerts to proactively identify potential issues before they affect customers.
• Participate in team meetings to provide updates on ongoing issues and contribute to process improvements.
• Maintain documentation of data engineering processes, data models, and system configurations.

Senior Data Engineer

Backend Engineer

• Develop, maintain, and optimize backend services using Node.js and TypeScript/JavaScript.
• Work with both SQL (PostgreSQL) and NoSQL (MongoDB) databases for data modeling, performance tuning, and query optimization.
• Build secure, scalable APIs to support frontend applications and third-party integrations.
• Implement containerized deployments using Docker and manage workloads in Kubernetes (K8s) environments.
• Collaborate with the DevOps team to follow GitOps practices for CI/CD pipelines and infrastructure as code.
• Design and implement features for CMS-driven, SaaS, and multi-tenant platforms.
• Write clean, maintainable, and testable code with proper documentation.
• Monitor system performance, troubleshoot issues, and ensure high availability and reliability.

Backend Software Engineer

Machine Learning Engineer

• Position Overview: ShyftLabs is seeking an experienced Senior Machine Learning Engineer to design and implement ML infrastructure and assess Agentic BI readiness for Fortune 500 enterprise companies. You will build robust MLOps platforms, design scalable ML pipelines, and provide strategic guidance for implementing autonomous business intelligence and AI-driven analytics systems.
• ShyftLabs is a growing data product company founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation.