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Lead technology and AI strategy for a growing SaaS company, oversee engineering and external teams, drive LLM and AI integration, scale architecture and infrastructure, improve development processes, manage budgets and vendors, ensure security and reliability, and recruit and mentor technical talent.

The role involves full-stack development with a focus on backend Java and frontend React. Responsibilities include guiding offshore developers, solving technical challenges, and communicating effectively with the team.

Build SME Studio interfaces for six MVP knowledge-capture exercises; implement validation, admin, and error-handling UI around Agent DNA; lay groundwork for review and explainability surfaces; collaborate with Product and Design on human-in-the-loop workflows and API integrations focused on clear interfaces for non-technical SMEs.

Lead design and implementation of an enterprise data quality framework using Great Expectations, creating Rule-as-Code validations, observability, lineage, CI/CD integration, dashboards, and remediation processes while collaborating with cross-functional teams to prevent and resolve data issues.

Serve as a product management/business analyst to gather and document business and technical requirements, create user stories and acceptance criteria, manage product backlogs, coordinate with distributed development teams, validate API integrations using testing tools, read C# when needed, and produce technical and end-user documentation to support platform initiatives and delivery.

Provide L3/BAU production support for web applications: troubleshoot incidents, debug .NET/C# code, perform root cause analysis, optimize SQL Server queries and SSRS reports, collaborate with development and infrastructure teams, manage deployments, and document support procedures.

Lead design, implementation, and operation of scalable AWS cloud infrastructure and automated CI/CD pipelines. Drive IaC (Terraform/CloudFormation), containerization (Docker/Kubernetes/ECS), configuration management (Chef/Puppet), monitoring, automation, and DevOps best practices across Agile engineering teams to improve reliability, security, and delivery velocity.

Remote role to research, extract, normalize, and deliver structured data from public and government sources. Build reusable scraping workflows, document sources and methods, troubleshoot acquisition issues, version-control code, and collaborate with stakeholders to provide accurate, repeatable outputs.

Lead design and implementation of an enterprise data quality and observability framework using Great Expectations. Build Rule-as-Code validations, integrate automated checks into ETL and CI/CD, implement monitoring, alerts, dashboards, and lineage. Investigate root causes, define governance, and collaborate with engineering, QA, product, and support to operationalize data validation and anomaly detection for critical datasets.

The Laserfiche Process Automation Specialist is responsible for developing workflows, eForms, and optimizing business processes within the Laserfiche platform by collaborating with stakeholders to meet organizational goals.