Lead AI Engineer

Insight Global • Saint Paul, MN • 6h ago

Job Description

The client is seeking a Lead AI Engineer to help design, build, operationalize, and scale enterprise AI solutions supporting b2b platforms/applications. This individual will serve as a senior technical contributor responsible for developing production-grade AI applications, orchestrating agentic workflows, and collaborating closely with business and technical stakeholders to deliver measurable business outcomes.

The ideal candidate combines strong software engineering fundamentals with hands-on experience building AI-powered applications, LLM solutions, conversational AI systems, and multi-agent architectures.

Responsibilities

AI Solution Design & Development

Architect and build end-to-end AI solutions utilizing LLMs, Agentic AI, and conversational AI technologies.

Design and implement multi-agent and orchestrated AI workflows.

Develop AI-powered applications that leverage structured and unstructured data sources.

Build scalable APIs and services supporting AI products.

Production Ownership

Own the full AI application lifecycle from design through deployment and monitoring.

Establish observability, performance monitoring, and model health practices.

Manage model evaluation, drift detection, and continuous improvement processes.

Ensure AI solutions meet security and governance requirements.

Leadership & Collaboration

Partner with business stakeholders to understand use cases and translate them into technical solutions.

Collaborate with engineers, data scientists, architects, and product teams.

Mentor team members and contribute to AI best practices.

Help drive adoption of AI capabilities across the organization.

Technical Innovation

Evaluate emerging AI technologies and frameworks.

Establish standards for agentic AI development and deployment.

Support experimentation, prototyping, and proof-of-concepts.

We are a company committed to creating inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity employer that believes everyone matters. Qualified candidates will receive consideration for employment opportunities without regard to race, religion, sex, age, marital status, national origin, sexual orientation, citizenship status, disability, 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 Human Resources Request Form. The EEOC "Know Your Rights" Poster is available here.

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 HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

6+ years of software engineering experience with Python.

Strong SQL and data engineering fundamentals.

Experience building and deploying AI, Generative AI, or LLM-powered applications.

Experience with prompt engineering and RAG architectures.

Hands-on experience creating conversational AI solutions.

Understanding of vector databases, embeddings, and semantic search.

Experience deploying applications in cloud environments.

Experience developing APIs and production-grade services.

Experience building AI workflows or AI agents.

Understanding of agent orchestration concepts.

Experience integrating LLMs into business applications.

Familiarity with model monitoring and AI application lifecycle management. - Experience building multi-agent AI systems.

Experience with Agent-to-Agent (A2A) architectures.

Experience utilizing MCP (Model Context Protocol).

Databricks experience.

Knowledge of MLOps practices.

Experience with model evaluation frameworks and AI observability tools.

Experience deploying enterprise-scale AI solutions.

Experience supporting Retail, QSR, Customer Experience, or Intelligence platforms.

Public GitHub projects demonstrating AI implementations.

Personal projects involving LLMs, agents, copilots, or autonomous workflows.

Traditional Machine Learning and Data Science background.

Experience mentoring engineers or serving as a technical lead.

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