Jobs at 66degrees

Build and deploy a modern AI-integrated application on GCP during a 12-week contract. Develop React/TypeScript frontends and Python/FastAPI backends, deploy services with Cloud Run and Cloud Run Jobs, integrate Vertex AI Gemini models, manage Firestore and BigQuery data, configure enterprise SSO with IAP and Microsoft Entra ID, and maintain Azure DevOps CI/CD pipelines.

Designs and implements Google Cloud database migration strategies, including architecture, data models, database objects, pipelines, orchestration, security, and data transfers. Advises customers on Cloud Spanner and Cloud SQL implementations, translates SQL and stored procedures, configures Google Cloud components, performs performance testing, resolves performance issues, and delivers technical workshops and architectural recommendations.

Lead customer-facing deployment of frontier-model and agentic AI solutions from discovery through production. Responsibilities include system design, full-stack coding, workflow automation, technical scoping, prototyping, demonstrations, stakeholder engagement, adoption, and production optimization. The role collaborates across Sales, Engineering, Product, Research, Security, GRC, Partnerships, and go-to-market teams while translating field feedback into product and model improvements.

Provide advisory architecture and migration strategy to consolidate multiple Microsoft 365 tenants into one enterprise tenant, lead Copilot rollout and integration, advise on Exchange, OneDrive, SharePoint, and Power Platform, identify risks and dependencies, and partner with client leadership to deliver migration planning and best practices.

Lead quality assurance for complex GCP data engineering pipelines. Design and implement integration, regression, end-to-end, database, and data-quality testing across BigQuery, dbt, Dataflow, Dataproc, Cloud Run, and related services. Automate testing in CI/CD pipelines, provision test environments with infrastructure as code, validate pipeline outputs, monitor system health, and improve data quality practices. Collaborate with engineers and stakeholders, mentor junior QA staff, and champion testing standards.

Lead QA for complex Google Cloud data engineering pipelines. Design and execute integration, regression, end-to-end, database, API, and data-quality testing across ETL/ELT systems. Automate testing through CI/CD, provision reproducible environments with infrastructure-as-code, validate pipeline outputs and database functions, and monitor system health. Collaborate with data engineers and stakeholders, mentor junior QA staff, and improve data quality and testing effectiveness.

Lead quality assurance for complex GCP data engineering pipelines. Design and execute integration, regression, end-to-end, database, API, and data-quality tests across tools including Dataflow, Dataproc, BigQuery, dbt, Cloud Run, and managed databases. Automate testing within CI/CD pipelines, provision reproducible environments with infrastructure as code, monitor pipeline health, validate data accuracy and performance, collaborate with data engineers, and mentor junior QA professionals.

Design, deploy, secure, and automate Apigee X API management workflows on GCP. Responsibilities include configuring API proxies, networking, security policies, secrets, TLS and mTLS, backend integrations, and multi-environment CI/CD pipelines. The engineer will also conduct API testing, trace and debug proxy executions, troubleshoot latency, and support monitoring and alerting. The five-week contract requires hands-on Apigee X and GCP expertise, with financial integrations, Google Apps Script, and observability experience preferred.

Design, deploy, and maintain scalable cloud and edge infrastructure on GCP and GDC, focusing on manufacturing environments. Build Infrastructure as Code automation, support Manufacturing Edge Connect and Data Hub architectures, establish CI/CD pipelines, and enforce security and compliance. Implement monitoring, logging, alerting, and disaster recovery while collaborating with data scientists, industrial engineers, and software developers. The role requires expertise in GCP, GDC, Kubernetes, cloud data services, networking, Terraform, scripting, and Linux and Windows administration.

Leads data science and machine learning architecture engagements, analyzing diverse datasets and deploying models using cloud and big data technologies. Designs scalable, cost-effective solutions, including generative AI applications, and provides technical leadership across client delivery and presales activities. Creates standards, accelerators, reports, and presentations; mentors junior staff; and communicates technical concepts to business stakeholders.

Designs, implements, and manages scalable Google Cloud data architectures using GCP services. Develops data models and large-scale processing solutions with Spark and Hadoop, builds optimized data pipelines, and establishes governance for quality, security, compliance, and metadata. Monitors system performance and collaborates with engineers, data scientists, and stakeholders to provide architectural guidance and identify innovative cloud and data technologies.

The Enterprise Account Executive will build customer relationships, manage accounts, drive sales of cloud and professional services, and forecast revenue effectively.

Designs and implements secure, reliable GCP environments and enterprise cloud architectures for strategic clients. Responsibilities include advisory relationships, requirements gathering, project scoping, solution design, architecture diagrams, cloud migration roadmaps, hybrid connectivity, CI/CD guidance, Kubernetes containerization, and client presentations. The role leads project meetings, promotes Google Cloud solutions, influences stakeholders, and travels to customer sites and industry events as needed.

Serve as a pre-sales technical advisor bridging sales, engineering, and delivery to design, propose, and ensure operational stability of cloud solutions (GCP preferred). Develop SOWs, lead technical presentations, build proofs-of-concept, support migrations, manage SLA and incident/RCA processes, and drive managed-services success and customer advocacy.

The Senior Solution Consultant designs and implements AI and cloud solutions for clients, collaborates with sales and engineering, and ensures successful project outcomes.

Lead a global Managed Services/SRE team to operate, scale, and improve multi-cloud (GCP/AWS/Azure) infrastructure, define operational processes and KPIs, manage on-call and capacity planning, maintain customer relationships and compliance (MSP/ISO/SOC2), and evolve service offerings.

Design, build, and maintain scalable, secure GCP infrastructure using IaC (Terraform/Deployment Manager). Implement CI/CD, monitoring, backup/disaster recovery, and security/compliance controls. Optimize performance, resolve complex infrastructure issues, document architectures, and collaborate with cross-functional teams to support data and AI workloads.

Sell cloud, AI, data, and professional services to enterprise customers. Build pipeline within assigned territory, engage executive sponsors, coordinate internal and partner resources, negotiate services/SOWs, forecast revenue, and drive adoption of cloud professional services to exceed quota.