Signature Aviation

Analyst

• Drive enterprise-wide operational improvement initiatives by analyzing workflows, leveraging data and performance metrics, and leading structured problem-solving efforts across functions.
• Ensure improvement initiatives are scalable, sustainable, and aligned with broader digital and AI-enabled transformation efforts.
• Establish measurement frameworks, develop executive-level insights, and influence leaders to embed continuous improvement practices into day-to-day operations.

Senior Continuous Improvement Analyst

Accountant

• Manage the full lifecycle of fixed assets, including capitalization, depreciation, transfers, retirements, and disposals.
• Review asset additions to ensure appropriate classification, useful lives, and depreciation methodologies.
• Perform monthly, quarterly, and annual fixed asset close activities, including reconciliations between the fixed asset subledger and general ledger.
• Prepare fixed asset rollforwards, depreciation schedules, and supporting documentation for financial reporting.
• Ensure compliance with U.S. GAAP, company accounting policies, and internal control requirements related to fixed assets.
• Serve as a key point of contact for internal and external auditors on matters related to fixed asset accounting.
• Prepare and respond to audit requests and inquiries in a timely and accurate manner.
• Identify opportunities for process improvements that enhance efficiency, accuracy, and control within the fixed asset accounting process.
• Support system implementations, upgrades, or enhancements related to ERP or fixed asset subledger systems.
• Maintain and update fixed asset accounting policies, procedures, and documentation.
• Partner with Construction & Infrastructure, IT, FP&A, Capital Management, Tax, and Operations teams to ensure proper capitalization and asset tracking.
• Provide accounting guidance related to capital projects, including construction-in-progress (CWIP) accounting and project closeouts.
• Support budgeting and forecasting activities related to capital expenditures and depreciation.

Senior Accountant, Fixed Assets

AI Engineer

• Design and implement cloud infrastructure supporting LLM platforms, vector databases, and model inference pipelines
• Build and operate scalable environments supporting agentic AI systems, predictive models, and enterprise AI applications
• Support AI-driven operational use cases such as dynamic pricing, demand forecasting, and ramp capacity optimization
• Implement and maintain MLOps pipelines supporting model training, deployment, monitoring, and lifecycle management
• Develop Infrastructure-as-Code environments using tools such as Terraform to enable scalable and repeatable deployments
• Optimize cloud performance, scalability, and reliability for AI and data workloads
• Implement monitoring, logging, and observability platforms to ensure operational visibility and system performance
• Collaborate with security and compliance teams to ensure data protection, platform security, and regulatory compliance
• Enforce cloud governance, cost optimization, and operational resilience best practices
• Design and support infrastructure for edge computing solutions that enable AI capabilities in field operations environments
• Partner with engineering, data science, and platform teams to ensure seamless integration between AI infrastructure and enterprise systems

Lead Cloud AI Platforms Engineer

Manager

• Oversee the acquisition and deployment of critical operational assets (e.g., fuel trucks, tugs).
• Develop lifecycle planning strategies, including standardization of brands, training, and maintenance.
• Monitor key performance indicators (KPIs) related to asset usage, uptime, and reliability.
• Manage preventive maintenance (PM) schedules to ensure equipment reliability and regulatory compliance.
• Implement quality control measures for maintenance checks and compliance verification.
• Oversee repair, overhaul, retirement, and redeployment strategies to optimize asset longevity.
• Ensure technical specifications align with training programs for proper asset usage and maintenance.
• Develop and enforce best practices and standard operating procedures (SOPs) in collaboration with OEMs.
• Maintain comprehensive documentation, including manuals, training modules, and knowledge-sharing resources.
• Lead contingency planning efforts for asset-related disruptions and emergencies.
• Develop and execute spare asset strategies to ensure operational continuity during critical events.
• Oversee emergency response planning, ensuring rapid deployment of resources when needed.

Operational Asset Manager

Recruitment

• Lead full life cycle recruiting for a broad range of positions from Director level to Executive Search for Signature Aviation.
• Partnering with the Director, Talent Acquisition, develop and execute a best-in-class executive recruiting process and strategy aligned with the organization’s long-term business objectives and culture.
• Implement creative sourcing strategies to fuel talent pipelines, build key networks, and create contemporary methods for tracking candidate research.
• Leverage emerging technologies, including AI, to enhance executive recruiting strategies and decision making.
• Create, lead, and execute the executive search process, govern and report on recruiting metrics, as well as search firm spend and cost avoidance.
• Provide an enhanced candidate experience, drawing top talent to our organization.
• Actively obtain feedback from key leaders on the execution of executive search processes and continuously identify and implement process improvements.

Lead Executive Recruiter

LLM Engineer

• Design, build, and deploy AI applications leveraging hosted or proprietary large language models.
• Lead technical design decisions for enterprise generative AI implementations, ensuring solutions are scalable, secure, and production-ready.
• Develop use cases such as:
• Natural language querying of enterprise data
• Document summarization and information extraction
• Conversational AI, copilots, and knowledge assistants
• Decision-support and workflow automation tools
• Develop APIs, microservices, and integrations to expose AI capabilities to internal platforms and applications.
• Ensure solutions are aligned with enterprise architecture, security, and engineering standards.
• Provide technical guidance and design reviews for other engineers contributing to AI-enabled applications.
• Design, test, and optimize prompts for accuracy, consistency, safety, and business alignment.
• Architect orchestration workflows that combine LLMs with external tools, APIs, structured data, and business logic.
• Implement guardrails to mitigate hallucinations, enforce policy constraints, and reduce prompt injection risks.
• Establish repeatable testing frameworks and evaluation methodologies for prompt and workflow performance.
• Drive best practices for prompt engineering, orchestration design, and model interaction patterns across engineering teams.
• Design and implement RAG architectures leveraging enterprise data sources.
• Build and maintain embedding pipelines, vector databases, and retrieval services.
• Ensure relevance, freshness, access control, and compliance for retrieved content.
• Optimize retrieval strategies and grounding techniques to improve response quality and accuracy.
• Provide architectural guidance on enterprise knowledge systems that support AI-driven applications.
• Deploy AI applications into production environments with robust CI/CD pipelines and infrastructure practices.
• Establish monitoring frameworks for:
• Model output quality and drift
• Latency, availability, and reliability
• Cost, usage, and scaling patterns
• Diagnose and resolve production incidents related to AI systems.
• Improve system robustness through testing, logging, and observability best practices.
• Guide engineering teams on operational standards for running reliable AI services in production environments.
• Implement safeguards for data privacy, security, and access control.
• Ensure AI systems comply with enterprise governance and regulatory standards.
• Support explainability, auditability, and responsible AI practices.
• Prevent leakage of sensitive or proprietary information in AI interactions.
• Partner with security, legal, and governance teams to establish guardrails for enterprise AI adoption.
• Partner closely with:
• Director of Data Science & AI
• Data Scientists and ML Engineers
• Data Engineers and Platform Engineers
• Legal, Security, and Governance teams
• Lead technical design discussions and architecture reviews for AI solutions.
• Participate in Agile delivery processes and guide implementation planning for complex AI initiatives.
• Communicate risks, trade-offs, assumptions, and limitations of AI solutions to both technical and non-technical stakeholders.
• Mentor engineers and contribute to the growth of AI engineering capabilities within the organization.

Lead AI, LLM Engineer

Data Scientist

• Develop and deploy predictive models supporting revenue forecasting, demand prediction, and operational planning
• Support dynamic pricing initiatives through machine learning models and pricing optimization algorithms
• Design and implement ramp capacity and operational optimization models to improve resource planning and throughput
• Develop data enrichment pipelines that enhance CRM, crew, and operational datasets with predictive insights
• Support enterprise AI platforms through the development of features, embeddings, and model inputs for LLM and RAG-based applications
• Design and implement experimentation frameworks to evaluate model performance and measure business impact
• Build and maintain scalable data pipelines supporting machine learning and analytics workloads
• Integrate predictive analytics and machine learning outputs into enterprise systems and operational workflows
• Maintain strong data governance, quality, and documentation standards across data science assets

Senior Applied Data Science Engineer

Systems Engineer

• Architect scalable agentic AI systems that enable intelligent automation and decision support across enterprise operations
• Design and implement AI solutions supporting dynamic pricing and revenue optimization initiatives
• Develop predictive systems that improve ramp capacity planning, operational throughput, and workforce utilization
• Engineer LLM-powered applications using retrieval-augmented generation (RAG), agent frameworks, and orchestration platforms
• Design AI-driven automation solutions that streamline operational workflows and task management
• Build and maintain pipelines that enrich enterprise datasets, including crew, customer, and CRM data platforms
• Integrate AI capabilities with enterprise platforms and operational systems
• Establish engineering standards and architectural patterns for AI and LLM-based application development
• Ensure responsible AI implementation, including governance, monitoring, and security considerations
• Provide technical leadership, architectural guidance, and mentorship to engineering teams building AI capabilities

Principal AI Agentic System Engineer

Platform Engineer

• Define and lead the enterprise AI platform strategy supporting revenue optimization, operations intelligence, and automation initiatives
• Build and lead high-performing AI engineering teams responsible for developing and scaling AI capabilities across the enterprise
• Drive the design and deployment of AI solutions enabling dynamic pricing, revenue optimization, and demand forecasting
• Lead development of predictive operational models to optimize ramp capacity, staffing, and operational throughput
• Establish enterprise data and AI architecture supporting scalable model deployment, orchestration, and monitoring
• Advance AI-driven data enrichment across CRM, crew, and operational data platforms
• Implement intelligent task orchestration and automation capabilities that improve operational efficiency across locations
• Establish governance frameworks for responsible AI, security, and model lifecycle management
• Partner with Product, Commercial, Operations, and Technology leadership to align AI capabilities with strategic business priorities
• Evaluate emerging AI technologies and platforms to continuously improve enterprise AI capabilities
• Communicate strategy, progress, and measurable business impact to executive leadership

Director, AI Agents – Platform Engineering

Data Analyst

• Collect, integrate, and validate data from multiple operational and safety systems to ensure accuracy and reliability
• Analyze safety and operational data to identify trends, performance gaps, and opportunities for improvement
• Develop dashboards and reports that track key performance indicators (KPIs) related to safety, ramp operations, and operational performance
• Partner with operational and safety leaders to translate data insights into actionable improvement initiatives
• Support development of predictive models and analytics that help anticipate operational risks and safety incidents
• Collaborate with IT and data teams to enhance data infrastructure and improve access to operational datasets
• Develop analytical frameworks that support operational forecasting, performance monitoring, and decision support
• Provide clear insights and recommendations to leadership based on data analysis and performance trends
• Work cross-functionally with Safety, Operations, IT, and Compliance teams to align analytics initiatives with operational priorities

Senior Data Analyst

• Translate business challenges into analytical approaches and technical solutions
• Develop statistical and machine learning models supporting initiatives such as demand forecasting, staffing optimization, and operational planning
• Build time series models and predictive analytics solutions to support operational and commercial decision-making
• Prepare, clean, and transform raw data into structured datasets suitable for statistical modeling and analysis
• Identify and incorporate new data sources and variables to improve model performance and predictive accuracy
• Translate model outputs into operational insights and measurable business KPIs
• Develop visualizations and reporting tools that communicate model results and insights to business stakeholders
• Integrate analytical outputs into operational workflows and decision-making processes
• Partner with cross-functional teams across operations, technology, and analytics to prioritize and execute data initiatives
• Build relationships with internal and external data and technology partners to enhance analytics capabilities

• Design and lead a comprehensive, enterprise-wide‑ Talent Acquisition Strategy, aligned to business priorities, workforce plans, and future skill requirements across executive, professional, and frontline populations.
• Translate business strategy and talent planning insights into differentiated sourcing, assessment, and hiring approaches in partnership with HRBPs and business leaders.
• Responsible for connecting across all global locations including US, Europe, Latin America to drive global processes and operational efficiency.
• Anticipate labor market shifts and evolving skill needs, using external talent intelligence and internal data to proactively shape recruiting strategy.
• Champion market leading‑ recruiting practices, including skills-based hiring, talent segmentation, structured and equitable‑ assessments, proactive talent communities, and continuous improvement of candidate experience.
• Advance the responsible use of recruiting technology, automation, and AI to improve speed, quality of hire, equity, and scalability.
• Establish enterprise frameworks, standards, and governance that ensure consistent, high-quality‑ recruiting outcomes across the organization.
• Develop and execute tailored search strategies for senior level executive roles leveraging direct sourcing, talent intelligence platforms, market mapping, and deep industry insights
• Lead and optimize the strategic partnership with the RPO provider, ensuring alignment to business needs, service levels, and evolving workforce priorities.
• Set clear performance expectations, metrics, and governance to ensure accountability, transparency, and continuous improvement across internal and external recruiting teams.
• Lead, coach, and develop a high performing‑ Talent Acquisition COE team, building enterprise capability and bench strength.
• Serve as a trusted advisor to leaders and hiring managers—raising capability in talent decision-making‑, inclusive hiring, and modern assessment practices.
• Foster a culture of accountability, collaboration, and continuous learning across the recruiting ecosystem
• Own recruiting performance end-to-end‑, using data, dashboards, and insights to measure outcomes, diagnose issues, and drive continuous improvement.
• Ensure compliance with employment regulations and uphold ethical, equitable, and inclusive hiring practices enterprise wide‑.

Director, Global Talent Acquisition

Product Manager

• Define the vision to translate business requirements into clear, actionable intent of our products for the technical teams.
• Conduct market research and competitive analysis to identify opportunities for product innovation and improvement.
• Develop and maintain a living product roadmap that balances immediate customer needs with the long-term enterprise goals.
• Lead the product development process, from ideation through design, testing, and launch.
• Prioritize product features and enhancements based on stakeholder feedback, market trends, and business objectives.
• Collaborate effectively with stakeholders across the enterprise to manage relationships and meet customer needs.
• Act as the primary point of contact for all product-related inquiries, fostering strong communication across departments.
• Provide context for IT to collaborate in real-time of the requirements to accurately build the product features.
• Leverage data to identify friction points in the current operational process to prompt the new wave of product enhancements.
• Partner with the customers to identify manual bottlenecks and prioritize to create smarter product logic.
• Collect diverse feedback from the customers, synthesize conflicting needs into a single, cohesive product direction.
• Drive organizational change by ensuring that training and ongoing support are included when a product launches.

Operational Excellence Product Owner

• Lead and guide the direction of defining the vision and strategy of safety products.
• Conduct market research and competitive analysis to identify opportunities for product innovation and improvement.
• Develop a product roadmap that aligns with organizational goals and customer needs across the enterprise.
• Lead the product development process, from ideation through design, testing, and launch.
• Prioritize product features and enhancements based on stakeholder feedback, market trends, and business objectives.
• Collaborate effectively with stakeholders across the enterprise to manage relationships and meet customer needs.
• Act as the primary point of contact for all product-related inquiries, fostering strong communication across departments.
• Partner with operational leaders to implement data-driven solutions that streamline processes and enhance efficiency.
• Showcase analytical skills to support data-driven decision-making and inform product strategies.
• Ensure that all products meet industry standards and regulatory compliance.
• Collaborate with cross-functional teams across the enterprise to collect requirements and feedback.
• Present product updates, strategy, and performance metrics to senior leadership and key stakeholders.
• Drive organizational change by providing training and ongoing support to improve safety and operational efficiency.

Product Manager – Safety & Operations Excellence

Sales

• The Director, Key Accounts will be responsible for developing new and existing relationships with Key Accounts and coaching Sales Managers on sales strategies, opportunities, and overall company direction.
• The Key Accounts team will be responsible for implementing strategic and tactical programs to enhance sales segment penetration and deliver value for customers and competitive advantage for Signature Aviation.
• This position will lead Sales Managers for Key accounts, developing a high-achieving team of motivated account managers and providing the tools and guidance to expand their knowledge and influence with customers.
• Along with Sales Managers, the Director of Key Accounts will also act as the voice of the customer within Signature Aviation, coordinating across teams and functions to develop optimal outcomes and grow the overall book of business.