Director, Artificial Intelligence & Software Engineering

Position Overview Pond & Company / Enercon Services, Inc. is seeking a visionary, execution-focused Director of Artificial Intelligence & Software Engineering to lead the strategy, development, and delivery of enterprise AI capabilities and software engineering initiatives across a growing multidisciplinary engineering, architecture, planning, environmental, and consulting organization of approximately 2,700 professionals. This leader will be responsible for building and scaling the organization's AI and software engineering functions, driving digital transformation, intelligent automation, enterprise application development, and AI-enabled innovation. The role requires a unique combination of strategic leadership, organizational influence, technical depth, and operational excellence. The Director will oversee the development of enterprise AI platforms, agentic systems, software products, automation frameworks, integrations, and digital solutions that improve operational performance, engineering productivity, project delivery, knowledge management, and client outcomes. Working closely with executive leadership, business units, operations, IT, cybersecurity, data, and engineering teams, this individual will help establish AI and software engineering as core strategic capabilities and competitive differentiators for the organization. Key Responsibilities Enterprise AI & Software Engineering Strategy Develop and execute a comprehensive enterprise strategy for Artificial Intelligence, software engineering, intelligent automation, and digital product development. Establish multi-year roadmaps for: AI adoption and enablement Enterprise software platforms Digital transformation initiatives Agentic AI systems Intelligent automation Knowledge management solutions Partner with executive leadership to align technology investments with business objectives and growth strategies. Identify opportunities to leverage AI and software solutions to improve operational performance, project delivery, client service, and innovation. Drive measurable business outcomes through technology initiatives focused on productivity, scalability, quality, and efficiency. Serve as a trusted advisor and thought leader on AI, software engineering, and emerging technologies. AI Platform & Intelligent Systems Leadership Lead development and deployment of enterprise AI capabilities leveraging: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) AI agents and multi-agent systems Workflow automation Predictive analytics Knowledge management platforms AI-assisted engineering and design solutions Establish standards for AI architecture, governance, observability, scalability, and lifecycle management. Evaluate emerging AI technologies and guide adoption of enterprise-ready solutions. Ensure AI systems are secure, governed, maintainable, and aligned with organizational standards. Oversee AI platform architecture and integration with enterprise systems. Software Engineering Leadership Lead and grow a high-performing software engineering organization responsible for enterprise applications, integrations, automation solutions, digital products, and AI-enabled platforms. Establish software engineering standards, development methodologies, architecture principles, and delivery frameworks. Drive adoption of modern engineering practices including: Agile development DevOps CI/CD Cloud-native architectures API-first development Platform engineering Oversee software architecture reviews and technical governance. Ensure software solutions meet performance, reliability, security, and scalability requirements. Guide build-versus-buy decisions and vendor technology evaluations. Team Leadership & Organizational Development Recruit, develop, mentor, and retain AI engineers, software engineers, architects, developers, and technical leaders. Build organizational capabilities in AI, software engineering, automation, and digital innovation. Foster a culture of collaboration, innovation, accountability, and continuous improvement. Establish career development frameworks and technical leadership pathways. Manage budgets, resource planning, staffing strategies, and vendor relationships. Business Transformation & Digital Innovation Partner with operational and business leaders to redesign workflows and business processes through AI and software solutions. Identify opportunities to improve: Project delivery efficiency Engineering productivity Knowledge management Proposal generation Document processing Data analytics and reporting Resource planning Client engagement Field operations Lead digital transformation initiatives from ideation through enterprise deployment. Develop frameworks for prioritizing technology investments based on business value, ROI, risk, and strategic alignment. Governance, Security & Risk Management Establish governance frameworks for AI systems, software development, and enterprise applications. Partner with cybersecurity, legal, compliance, and risk management teams to ensure responsible technology deployment. Develop policies related to: AI governance Data privacy Software security Intellectual property protection Third-party technology management Responsible AI practices Ensure compliance with regulatory requirements, client expectations, and industry standards. Qualifications Required Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Engineering, Data Science, or a related field. 10+ years of progressive leadership experience in software engineering, technology, AI, digital transformation, or related disciplines. 5+ years of leadership experience managing software engineering teams, technical organizations, or digital product development functions. Demonstrated success leading enterprise software development and AI initiatives from strategy through implementation. Strong expertise with modern software engineering and AI technologies, including: Enterprise application development Cloud-native architectures APIs and integrations DevOps and CI/CD LLMs and Generative AI AI agents and orchestration frameworks RAG architectures Vector databases Workflow automation platforms Cloud AI services Experience leading cross-functional enterprise initiatives and organizational change efforts. Strong technical credibility with the ability to engage deeply with engineers, architects, and executive stakeholders. Experience managing technology budgets, vendor relationships, and strategic technology investments. Proven ability to balance strategic leadership with operational execution. Preferred Master’s degree in Computer Science, Engineering, Business Administration, Data Science, or related field. Experience within engineering, architecture, construction (AEC), energy, utilities, environmental, industrial, or professional services organizations. Experience building and scaling internal software engineering teams. Experience implementing enterprise AI platforms, copilots, knowledge systems, or intelligent automation solutions. Familiarity with Azure AI, OpenAI, Microsoft Copilot ecosystem, AWS AI/ML services, LangChain, LangGraph, vector databases, and enterprise automation platforms. Experience leading enterprise modernization or digital transformation programs. Leadership Competencies Strategic and forward-thinking technology leader Strong execution and operational discipline Exceptional people leadership and talent development skills Entrepreneurial mindset with a bias toward innovation Collaborative and influential across all organizational levels Strong systems-thinking and problem-solving abilities Technically credible and business-oriented Effective communicator capable of translating technology investments into business value Comfortable leading through ambiguity and organizational change Success Metrics Success in this role will be measured by: Enterprise adoption and impact of AI and software solutions Delivery of strategic software engineering initiatives Operational efficiency improvements across the organization Productivity gains enabled through AI and automation Quality, reliability, and scalability of enterprise applications AI governance and software engineering maturity Innovation pipeline development and execution Business value realization and ROI from technology investments Growth and retention of high-performing engineering teams Advancement of digital transformation objectives