Senior Applied AI Engineer

Job Description

Seeking a Senior Applied AI Engineer to design, deliver, and strategically evolve enterprise-grade AI and GenAI solutions that integrate into an agentic AI ecosystem. This role blends technical leadership with strategic ownership across pricing, supply chain, merchandising, and customer experience initiatives.

The role is responsible for driving both hands-on execution and coaching team members across the Data & Analytics organization. You will lead AI-led code assistance, conversational interfaces, AI-assisted analytics, and agent-based solutions.

This position ensures that AI and GenAI capabilities are production-ready, scalable, and aligned with the organization's enterprise AI strategy.

Key Responsibilities:

• Lead the strategy, roadmap, and implementation of AI and GenAI solutions within an agentic AI ecosystem.

• Design and deliver scalable, production-ready AI solutions that drive automation, decision support, and business value.

• Establish standards, architectures, and best practices for agent-ready and orchestration-ready AI platforms.

• Partner with business, product, engineering, and MLOps teams to translate business needs into AI-enabled solutions.

• Ensure AI solutions meet governance, security, reliability, compliance, and operational excellence requirements.

• Develop reusable AI components and frameworks to accelerate adoption and reduce time-to-market.

• Drive enterprise adoption of GenAI, intelligent agents, and AI-assisted development practices. • Mentor and enable engineers and data scientists through coaching, training, and AI best practices.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

• Bachelor's or Master's degree in a technical or quantitative field.

• 5+ years of experience designing and delivering AI-driven solutions in enterprise environments.

• Proven ability to translate business problems into AI-enabled and automation-ready solutions.

• Experience building AI components within AI/ML and LLM orchestration pipelines, including tool/function calling, routing, and workflow integration with enterprise systems.

• Strong background in data science, machine learning, feature engineering, software development, experimentation, prototyping, and scaling AI solutions.

• Deep understanding of AI and GenAI applications within automated workflows, agentic systems, and multi-agent environments.

• Experience managing the AI solution lifecycle from design through deployment, monitoring, and continuous improvement in MLOps environments.

• Familiarity with governance, risk, compliance, and responsible AI practices.

• Strong collaboration skills across Data Science, MLOps, Platform, Engineering, and Product teams.

• Hands-on experience with AI-assisted development, conversational AI, AI-assisted analytics, and intelligent agent solutions.

• Practical experience with modern LLM frameworks such as LangChain, LlamaIndex, and Semantic Kernel.

• Demonstrated ownership, technical leadership, stakeholder influence, and mentoring experience. • Experience leading the design and scale-out of agentic AI platforms, orchestration frameworks, or AI workflow engines.

• Experience architecting solutions that combine traditional machine learning and GenAI capabilities.

• Exposure to intelligent automation and AI-driven business process transformation.

• Working knowledge of APIs, data pipelines, and AI service integrations.

•Experience implementing responsible AI and governance frameworks in production environments.