Jobs at ShyftLabs

Lead end-to-end delivery of large-scale cybersecurity and technology programs across enterprise teams. Manage plans, timelines, dependencies, risks, resources, metrics, and executive communications. Facilitate Agile ceremonies, support Scrum teams, translate technical requirements into delivery plans, and resolve cross-functional roadblocks. Partner with engineering, cybersecurity, infrastructure, compliance, and business stakeholders while applying Agile, Waterfall, or hybrid methodologies.

Lead enterprise QA strategy, automation framework development, testing, and release readiness across web, mobile, API, retail, and POS applications. Build and scale Playwright-based E2E frameworks, apply Claude and other generative AI tools to improve test generation and maintenance, oversee test automation and manual testing, mentor QA engineers, manage defect triage and code reviews, and partner with engineering and business teams throughout delivery cycles.

Build and maintain scalable Databricks ETL/ELT pipelines using Python, PySpark, and SQL. Integrate databases, Amazon S3, files, and REST APIs; develop Delta Lake models using Medallion Architecture; manage Databricks Jobs and Workflows; optimize Spark performance; implement data quality, monitoring, error handling, and dimensional modeling; and collaborate with cross-functional teams on production-ready data solutions.

Lead the design, development, and optimization of scalable Databricks ETL/ELT pipelines. Integrate data from databases, S3, files, and REST APIs; implement Delta Lake medallion architecture, Unity Catalog, dimensional models, data quality controls, and Spark performance tuning. Schedule and monitor Databricks workflows, collaborate cross-functionally, and guide engineers while driving technical decisions.

Source, screen, and hire technical talent across software engineering, DevOps, data science, machine learning, cybersecurity, and other specialized roles. Partner with hiring managers, develop sourcing strategies, assess technical skills and cultural fit, guide candidates through the hiring process, and monitor recruiting market trends.

Own strategy, vision, roadmaps, and execution for technically complex data, cloud, and AI products. Lead discovery through launch, define requirements and success metrics, make prioritization and build-versus-buy decisions, and partner with engineering, architecture, data, and AI/ML teams. Serve as the senior product contact for Fortune 500 clients, lead distributed delivery teams, manage dependencies and stakeholders, and mentor junior product professionals.

Develop and maintain Power BI and Looker dashboards, reports, data models, and analytical assets. Analyze complex datasets with SQL and Python, validate data quality, translate stakeholder requirements into actionable insights, and support project milestones. Collaborate with technical and business teams, optimize BI performance, communicate findings, and explore machine learning applications in business analytics.

Own the roadmap and lifecycle of data and AI products, from enterprise discovery and problem definition through delivery, launch, and iteration. Translate business needs into product requirements, partner with engineering, data engineering, and design, define measurable outcomes, lead Agile ceremonies, prioritize feedback-driven improvements, and communicate risks and trade-offs to stakeholders. The role also contributes to product discovery, prioritization, and delivery practices.

Lead design, architecture, and delivery of enterprise-scale data platforms using Databricks and Spark. Architect Lakehouse solutions, build ETL/ELT pipelines, implement IaC and CI/CD, ensure data governance and security, mentor engineers, and partner with Fortune 500 clients from discovery through production.

Design, build, and scale data-driven platforms and systems, focusing on backend and frontend engineering, integrations, and AI capabilities.

The DevOps Engineer will optimize cloud computing solutions, enhance infrastructure performance, ensure high availability, and manage CI/CD tools while collaborating with development teams.

The Associate AI Engineer will assist in building AI-powered backend services, integrating APIs, and developing data pipelines while collaborating with experienced engineers and teams.

Build and maintain backend-first platform features using Python and FastAPI, including REST APIs, PostgreSQL data models, multi-tenant access patterns, async workers, third-party integrations, and webhooks. Write comprehensive unit, integration, and async tests; participate in code reviews and architecture discussions; support production on-call, incident resolution, runbooks, and post-mortems.

Lead design, build, and operation of cloud infrastructure, CI/CD pipelines, and platform tooling. Implement IaC (Terraform), automate deployments, troubleshoot live systems, maintain monitoring/logging, mentor engineers, set DevOps technical direction, and evaluate new tools.

Work on building production-ready agentic AI applications and the Continuum platform: agent orchestration, model routing, persistent memory, tool integrations, retrieval pipelines, guardrails, evaluation, observability, and backend/APIs. Write well-tested Python code and contribute to open-source examples and documentation.

Seeking a Data Engineer to design and maintain ETL pipelines, data models, and infrastructure for analytics, working with enterprise clients.

Seeking a motivated Software Developer to design and develop software applications, collaborate on architectural standards, and engage in agile practices.

Lead DevOps Engineer will design and maintain scalable AWS infrastructure, own Terraform-based IaC, build CI/CD pipelines (GitHub Actions), automate with Python/Shell, implement GitOps and security practices, manage monitoring and incident response, drive disaster recovery and cost optimization, and lead/mentor a DevOps team.

Own strategy, roadmap, and delivery of analytical data products. Lead client discovery, prioritize backlogs, run Agile ceremonies, and ensure launches. Collaborate with engineering and data teams on data quality, governance, architecture (Snowflake, BigQuery, ClickHouse, Databricks, Redshift), perform SQL validation, and drive product adoption and continuous improvement.

Design, develop, and optimize big data solutions using Databricks, Apache Spark, and cloud platforms. Collaborate with teams to ensure high-performance data architectures.