Position Summary:       

In the Senior AI Engineer position, you’ll lead the development of intelligent, adaptive, and scalable applications by leveraging AI-powered development tools, machine learning models, and automation frameworks. Beyond writing code, you will play a key role in setting technical direction, mentoring engineers, and driving AI-first software strategies. You’ll work on a cross-functional team dedicated to creating high-quality, scalable web-based products, mobile applications, or server-based systems. As a senior engineer, you will take ownership of complex AI-enhanced solutions, influence architectural decisions, and advocate for AI-driven development methodologies. Your leadership will help the team develop a deep understanding of business context, financial trade-offs, and the strategic impact of AI-powered solutions. 

Skills Needed: 

• Applies AI and Technology – Identifies opportunities to boost efficiency and add value using AI and tech. Embraces and applies digital innovations and tech solutions to build business. Eagerly learns and integrates new technologies where they matter most. 

• Champions Innovation – Propels teams to unlock value with cutting-edge, tech-enabled innovations. Stays ahead of the tech curve, ready to embrace the next big thing. Leads with an entrepreneurial mindset and takes calculated risks. 

• Leads Through Change & Ambiguity – Navigates the unknown with confidence, steering through change and uncertainty with a clear vision and unwavering determination. 

• Ability to mentor and lead engineers in AI-first development methodologies, fostering a culture of innovation and technical excellence. 

• Technical expertise in AI integration across natural language processing, computer vision, and generative models. 

What You’ll Do and Impact:  

• Lead and mentor engineers in AI-first development methodologies and best practices. 

• Architect and scale AI-enhanced systems, ensuring security, scalability, and high performance. 

• Integrate AI-driven capabilities such as chatbot assistants, image-based diagnostics, and automated content creation into products. 

• Drive adoption of AI-powered engineering tools (e.g., LLM-augmented IDEs, automation frameworks) to enhance development efficiency. 

• Implement observability and monitoring systems to track AI application performance and ensure proactive issue resolution. 

• Design and optimize AI-driven APIs and microservices for seamless interaction with models, applications, and databases. 

• Stay engaged with AI and engineering communities, bringing cutting-edge practices and insights back to the team. 

• Mentor engineers on technical execution, business impact, and AI-first strategic thinking. 

• Balance execution speed with innovation, rapidly testing and iterating AI-driven features. 

• Work in an agile environment, ensuring high-quality, scalable software solutions. 

Experience: 

• 3-5+ years of software development experience, including 2+ years working on AI-powered applications or AI-integrated solutions. 

• Bachelor’s degree in Computer Science, Computer Engineering, or a related field. 

• Hands-on experience developing and deploying AI-driven applications (provide examples using models like Hugging Face or APIs like OpenAI, Anthropic). 

• Proficiency in Microsoft environments (Visual Studio, VS Code) and cloud services (AWS, Azure) for scalable AI applications. 

• Strong understanding of AI model cost optimization, infrastructure scaling, and performance tuning. 

• Experience integrating LLMs, agentic workflows, and autonomous AI systems into production environments. 

• Proven ability to mentor engineers and lead AI-first engineering transformations. 

Additional Items of Interest: 

• Contributions to open-source AI projects or AI research. 

• Experience with agentic AI frameworks (LangChain, AutoGPT). 

• Thought leadership through conferences, research, or industry engagement in AI-first development. 

• Expertise in AI-powered UI/UX development and human-computer interaction. 

• Strong proficiency in containerization (Docker, Kubernetes) and cloud-native AI deployments. 

• Diligence in unit testing, integration testing, and AI-driven problem-solving.