Senior Manager, Global Digital & Technology Systems Engineering
New
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JobgetherPharmaceutical R&D
Remote work opportunity within the United States.Full-TimeManager
SalaryBase salary range of $136,900–$181,900 annually
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Job Details
- Experience
- 7+ years of professional experience in systems engineering, cloud, infrastructure, digital technology, AI, data, integration, platform engineering, or a related technical delivery field
- Required Skills
- AWSDockerPythonSQLKubernetesMicrosoft AzureCI/CDRESTful APIsGenerative AI
Requirements
- Bachelor’s degree or higher in a relevant technical discipline.
- 7+ years of professional experience in systems engineering, cloud, infrastructure, digital technology, AI, data, integration, platform engineering, or a related technical delivery field.
- Experience coordinating complex technical work across cross-functional, matrixed, vendor, Enterprise IT, and engineering teams.
- Hands-on experience with externally developed platforms, SaaS solutions, integration architectures, cloud or hybrid infrastructure, observability, and application lifecycle management.
- Strong programming experience with Python and SQL for automation, data integration, API testing, scripting, and technical troubleshooting.
- Working knowledge of JavaScript/TypeScript and Bash or PowerShell.
- Practical understanding of REST APIs, event-driven integrations, JSON/XML data exchange, authentication, and secure system-to-system connectivity.
- Experience with AWS and/or Azure, including compute, storage, networking, identity, access controls, monitoring, and resource management.
- Familiarity with Docker, Kubernetes, and infrastructure-as-code or configuration-management tools such as Terraform, CloudFormation, or Ansible.
- Experience with Git, CI/CD pipelines, branching strategies, code reviews, automated testing, release management, and environment-promotion practices.
- Technical understanding of HPC, Linux environments, job schedulers, storage layers, and compute-intensive scientific workloads.
- Hands-on exposure to ML, AI, and generative AI implementation and deployment patterns, including RAG, embeddings, vector databases, semantic search, model integration, secure AI gateways, and agentic workflows.
Responsibilities
- Execute systems engineering activities across on-premises, hybrid cloud, vendor-hosted, and multi-tenant SaaS environments.
- Coordinate technical designs, dependencies, environments, access, implementations, and issue resolution with Enterprise IT, cybersecurity, vendors, and R&D stakeholders.
- Develop and maintain technical documentation, integration designs, deployment plans, runbooks, decision records, and lifecycle artifacts.
- Coordinate secure integrations among third-party platforms, internal applications, scientific workflows, data pipelines, and R&D technology environments.
- Implement observability and supportability capabilities, including monitoring, telemetry, dashboards, alerting, runbooks, and incident-management processes.
- Support configuration, deployment, validation readiness, and operational handoff for HPC clusters, containerized environments, storage platforms, data lakes, and pipelines.
- Manage patch coordination, release preparation, configuration documentation, automated deployment inputs, and transitions to steady-state operations.
- Implement approved AI and machine-learning patterns, including RAG pipelines, vector stores, semantic retrieval, embeddings, secure AI gateways, and multi-agent orchestration.
- Support infrastructure modernization, cloud migration, integration, and platform-adoption initiatives, including impact assessments, cutover plans, and support handoffs.
- Apply security, architecture, compliance, data protection, intellectual property, and operational controls to assigned systems and platforms.
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