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Are you ready to be part of a company that's not just talking about the future, but actively shaping it? Join The AES Corporation (NYSE: AES), a Fortune 500 company that's leading the charge in the global energy revolution. With operations spanning 14 countries, AES is committed to shaping a future through innovation and collaboration. Our dedication to innovation has earned us recognition as one of the Top Ten Best Workplaces for Innovators by Fast Company in 2022. And with our certification as a Great Place to Work, you can be confident that you're joining a company that values its people just as much as its groundbreaking ideas.
AES is proudly ranked #1 globally in renewable energy sales to corporations, and with $12.7B in revenues in 2023, we have the resources and expertise to make a significant impact as we provide electricity to 25 million customers worldwide. As the world moves towards a net-zero future, AES is committed to meeting the Paris Agreement's goals by 2050. Our innovative solutions, such as 24/7 carbon-free energy for data centers, are setting the pace for rapid, global decarbonization.
If you're ready to be part of a company that's not just adapting to change, but driving it, AES is the place for you. We're not just building a cleaner, more sustainable future - we're powering it. Apply now and energize your career with a true leader in the global energy transformation.
At AES, our commitment to a sustainable future in renewables drives us to explore the frontier of artificial intelligence. As pioneers in clean energy, we harness data, analytics, and cutting-edge agentic AI – autonomous intelligent agents – to optimize operations, anticipate challenges, and accelerate the transition to zero carbon. Joining our Renewables Data, AI & Analytics team, means being part of an innovative environment where you will help shape the next generation of intelligent systems for energy.
Summary of the Position
As the Agentic AI Strategist Specialist, you will spearhead the design, development, and deployment of agentic AI solutions tailored to the unique challenges and opportunities within the renewable energy sector. Reporting to the Clean Energy Digital Data & AI Solutions Manager, you will leverage your expertise in autonomous intelligent agents, machine learning, and AI strategy to realize measurable business value. Your role will blend strategic vision with hands-on innovation: driving projects that empower our teams through intelligent agents that learn from data, reason about complex renewable systems, and act autonomously to optimize operations, forecasting, maintenance, market participation, and customer engagement. Aligned with our operating model, you will collaborate cross-functionally to integrate agentic AI into core processes, enable seamless interactions between humans and AI agents, and embed Responsible AI principles into every stage of the lifecycle.
Key Responsibilities
Develop and drive agentic AI strategies that align with AES Renewables’ mission and business objectives.
Design, prototype, and deploy autonomous intelligent agents using advanced development platforms like Copilot Studio or Gemini Enterprise, along with all necessary programming components and automations to support the solutions.
Collaborate with engineering, operations, data science, and business teams to identify high-impact use cases for agentic AI across the renewable energy value chain (e.g. grid optimization, predictive maintenance, market bidding, trading analytics, asset management).
Lead cross-functional projects from concept through production, ensuring alignment with our Clean Energy operating model and realizing tangible improvements in efficiency, reliability, and cost-effectiveness.
Design and enforce an end-to-end agentic AI framework, establishing best practices, tools, and governance for safe, robust, interpretable, and adaptive AI agents.
Uphold Responsible AI principles explicitly for agentic systems: fairness, transparency, accountability, safety, bias mitigation, privacy, and regulatory compliance.
Monitor and evaluate deployed agentic solutions, iterate based on feedback and measured performance, and proactively address emergent risks or unintended behaviors.
Serve as a strategic advisor to senior leadership including the Clean Energy Chief Digital Officer, Data, AI & Analytics Senior Manager and Data & AI Solutions Manager on matters of agentic AI and its role in advancing our renewable mission.
Qualifications and Experience
Bachelor’s Degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or related discipline; advanced degrees are highly preferred.
2+ years of professional experience in Data Science, Machine Learning, or AI, including hands-on development of agentic or autonomous systems.
Proven track record of delivering impactful AI solutions, with at least 2 years in the renewable energy or related cleantech sector preferred.
Deep familiarity with reinforcement learning, multi-agent systems, natural language processing, conversational AI, and planning architectures.
Fluency in programming languages such as Python (with libraries like TensorFlow, PyTorch, RLlib), familiarity with cloud platforms (GCP, Azure), and scalable architecture.
Hands-on experience with advanced agent development platforms such as Microsoft Copilot Studio, Google AgentSpace, or similar frameworks is highly valued.
Familiarity with designing, deploying, and managing agent workflows in these environments, including integrating them with enterprise data sources and automation pipelines
Experience integrating data visualization and analytics tools (Power BI, Looker) with AI agents to surface actionable insights.
Demonstrated leadership, collaboration, and project management skills, mentoring a team or peers toward high performance and innovation.
Certifications in Responsible AI, AI Ethics, or Data Management (e.g. CDMP) are desirable pluses, alongside RL or AI safety certificates.
Strong communication and interpersonal abilities, enabling you to bridge technical and business domains effectively.
Willingness to travel as required to collaborate with field teams, partners, and stakeholders.
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