AI Engineer, Agentic Systems
FuelCell Energy, Inc.20 hours ago
Danbury, CT, USASenior
Base Salary
$100k - $115k/yr
Responsibilities
- Design, build, and deploy AI agents and multi-step agentic workflows that reason over enterprise data and act through integrated tools and systems.
- Translate business needs into AI solutions from problem framing and prototyping through evaluation, production deployment, and ongoing operations.
- Develop LLM applications using retrieval-augmented generation, prompt engineering, function and tool calling, and orchestration frameworks.
- Build supporting data pipelines, vector stores, connectors, APIs, and enterprise tool integrations.
- Establish testing, evaluation, guardrails, logging, monitoring, observability, and human-in-the-loop controls for AI solutions.
- Partner with Cybersecurity, IT, manufacturing, OT, and business teams on secure, governed, adopted, and maintainable AI solutions.
- Own deployed AI solution lifecycles, including versioning, performance tuning, prompt and model updates, and continuous improvement.
- Evaluate AI models, agent frameworks, Microsoft Copilot, and Copilot Studio and recommend fit-for-purpose approaches.
- Help define the AI roadmap, prioritize use cases, establish reusable standards and architectures, and advise leadership on capabilities and risks.
- Create technical documentation, reusable patterns, and coaching, and provide technical leadership for AI and automation projects.
Requirements
- Bachelor’s degree in computer science, software engineering, data science, or a related discipline, with extensive experience accepted in lieu of a degree.
- At least five years of software or AI/ML engineering experience, including hands-on delivery of production AI or agentic solutions integrated with enterprise data and systems.
- Demonstrated experience designing AI agents and agentic workflows using multi-step reasoning, tool or function calling, and orchestration frameworks.
- Experience developing LLM applications with RAG, prompt engineering, embeddings, vector databases, and model-output evaluation.
- Strong software engineering fundamentals, including Python, APIs, version control, testing, and maintainable production-grade code.
- Experience integrating AI solutions with enterprise data sources, applications, and platforms through APIs, connectors, and data pipelines.
- Experience with cloud AI services, particularly Microsoft Azure AI, and familiarity with Microsoft Copilot and Copilot Studio.
- Knowledge of machine learning concepts and practical tradeoffs involving model selection, accuracy, cost, latency, and reliability.
- Knowledge of AI safety, security, governance, data protection, access controls, guardrails, and responsible-AI principles.
- Experience evaluating, monitoring, and improving deployed AI solutions, including observability, guardrails, and performance tuning.
- Preferred certifications include Microsoft Azure AI, Azure AI Engineer, data science, machine learning, or comparable AI/ML credentials.
- Excellent communication, documentation, structured problem-solving, judgment, attention to detail, and ability to explain AI concepts to nontechnical stakeholders.
- Ability to work in office, manufacturing, warehouse, and data center environments; wear required PPE; and occasionally travel or work outside core hours.
Benefits
- Hybrid position based in Danbury, Connecticut, with regular onsite presence.
- Comprehensive benefits including medical, dental, vision, company-paid life and disability insurance, a 401(k) plan, employee stock purchase plan, and generous paid leave.
- Employment is contingent on completing a drug screen, criminal background check, and employment and education verification.
Categories
About FuelCell Energy, Inc.
FuelCell Energy designs, manufactures, and services megawatt-scale stationary fuel cell platforms that generate electricity, heat, hydrogen, and enable carbon capture for utilities, industrials, and municipalities. The company sells equipment and long-term service, and also develops, owns, and operates projects under power purchase and hydrogen supply agreements. Founded in 1969 and headquartered in Danbury, Connecticut, it is a publicly traded company on NASDAQ.