Serve as a subject matter expert for enterprise technologies, providing advanced technical leadership and leading architecture, design, integration, and implementation of scalable enterprise observability solutions.
Compensation
The expected base salary for this position ranges from $67.17 - 111.94/hour.
Responsibilities
Lead the architecture, design, integration, and implementation of scalable enterprise observability solutions using Dynatrace and IBM SevOne
Implement AIOps capabilities, including Dynatrace Davis AI, causal analysis, anomaly detection, intelligent automation, and AI-driven root cause analysis
Manage observability data, including logs, metrics, events, and alerts, ensuring effective telemetry governance, alert optimization, and cost control
Partner with business stakeholders, technology teams, and vendors to gather requirements and deliver complex technical solutions
Establish technology standards, architecture guidelines, and industry best practices
Requirements
Bachelor's degree in Computer Science, Computer Engineering, or a related field
Lead Engineer for Enterprise Applications responsible for driving design, development, modernization, and lifecycle management of enterprise application portfolios.
Responsibilities
Lead end-to-end delivery of web, mobile, and cloud-native applications
Define and govern technical architecture, development standards, and technology stack selection
Drive Agile execution including sprint planning, backlog refinement, and release management
Incorporate AI-assisted development tools to improve engineering productivity and quality
Evaluate and integrate AI/ML capabilities into applications
Requirements
Bachelor’s degree in computer science, Software Engineering, or related field (Master’s preferred)
Lead the development and execution of AI-driven products that modernize business processes and enable scalable automation across enterprise functions, partnering with engineering, data science, and business stakeholders.
Responsibilities
Execute the applied AI product roadmap aligned to enterprise AI strategy and platform priorities
Translate business needs into product requirements, backlog priorities, and release plans
Identify opportunities for AI-enabled automation within specific domains or workflows
Work with engineering and data science to refine technical solutions and product features
Translate operational challenges into AI-enabled features, automation workflows, or decision-support tools
Requirements
Bachelor's degree in STEM or related discipline
Bachelor's degree in a technical related field, typically Engineering or CS degree
The Enterprise Intelligence Manager is responsible for executing the Credit Union's enterprise data, analytics, artificial intelligence (AI), and automation strategies.
Responsibilities
Execute the Credit Union's enterprise intelligence strategy encompassing data, analytics, artificial intelligence, automation, and decision intelligence.
Translate strategic priorities into actionable initiatives, roadmaps, and measurable outcomes.
Establish and manage a portfolio of intelligence initiatives aligned with organizational goals.
Monitor performance and ensure initiatives deliver expected business value and strategic impact.
Regularly communicate progress, outcomes, and recommendations to AI Center of Excellence, project teams and CU leadership.
Lead a high-performing technology delivery organization responsible for delivering enterprise technology solutions and driving strategic business outcomes. Oversee end-to-end delivery, Agile and SDLC execution, release management, risk mitigation, and operational excellence initiatives.
Responsibilities
Lead, coach, and develop high-performing technology teams, including talent development, workforce planning, and performance management.
Oversee delivery of technology solutions, software releases, and strategic business initiatives.
Lead the development and execution of AI-driven technology strategies aligned with business objectives and product roadmaps.
Drive adoption of AI-enabled capabilities across technology teams to accelerate innovation, improve customer outcomes, and deliver measurable business value.
Champion AI adoption across the SDLC through AI-assisted engineering, testing, automation, and operational practices.
Requirements
Bachelor’s degree (B.E./B.Tech) in Computer Science, Information Technology, or related field
Master’s degree in Technology, Business Administration, or equivalent
Senior leadership and end-to-end accountability for CMC's scientific data, application, and AI product portfolio, leading a multidisciplinary team spanning engineering, data, product management, and agentic AI product strategy.
Lead client delivery for complex technology and AI programs, translating strategy into action through standardized, scalable implementation frameworks.
Compensation
A reasonable estimate of the current salary range is $180,000 - $247,500. In addition to your base salary, you will also be eligible for an annual discretionary performance bonus.
Responsibilities
Lead end-to-end delivery of complex TrinityEDGE deployments and AI-enabled solutions for priority US and global clients
Translate client strategies and commercial objectives into technical roadmaps, solution architectures, and phased implementation plans
Partner with the Head of Client Tech to institutionalize best practices in deployment, customization, and post-launch operations
If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges from $232,650 to $387,750.
Responsibilities
Provide senior leadership and line management for the CMC Scientific Data & AI Products team
Own overall accountability for the team's delivery, quality, and value realization
Set and communicate the integrated strategy and roadmap for CMC's data, application, and agentic AI product portfolio
Lead, coach, and develop direct reports and their teams
Act as the senior escalation point and decision-maker for cross-functional trade-offs
Requirements
Bachelor's degree in computer science, Data Science, Data Engineering, Artificial Intelligence/Machine Learning, Bioinformatics, Engineering, Life Sciences, or a closely related scientific or technical field
Master's degree or PhD in a scientific, data science, AI/ML, or engineering discipline (preferred)
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