Principal AI Engineer – Agentic AI, LangChain/LangGraph, Python

Principal AI Engineer – Agentic AI, LangChain/LangGraph, Python KORE1, a nationwide provider of staffing and recruiting solutions, has an immediate opening for a Principal AI Architect / Engineer – Agentic AI, LangChain/LangGraph, Python .

Location

Detroit / Southeast Michigan Work Arrangement: Primarily remote with in-person collaboration 2–4 times per month, up to 1 day per week Compensation: $184,000–$200,000/year base salary + 15% target bonus + RSUs targeted at 60% of annualized base salary Work Authorization: Applicants must be currently authorized to work in the United States.

The employer is unable to provide employment visa sponsorship or support visa transfers for this position, now or in the future. Position Summary The Principal AI Engineer will own the architecture and hands-on engineering of the company's AI and automation platform, with a primary focus on production autonomous AI agents.

This individual will assess business and technical needs, define the architecture and technical roadmap, evaluate emerging technologies, and personally design, build, deploy, and support AI agents and agentic solutions.

The role requires a strong software engineering foundation combined with current hands-on experience building production AI agents, preferably using LangChain and LangGraph or comparable production agent frameworks.

This individual will work across an evolving AI ecosystem and integrate agents with enterprise applications, APIs, tools, and governed data sources to develop reliable, scalable AI solutions supporting research, R&D, patent analysis, accounting, and other business processes. This is an individual contributor role combining AI architecture with hands-on engineering.

When larger implementations require additional capacity, external resources may be utilized, but this role retains direct architectural and engineering ownership of the AI platform and solutions.

Key Responsibilities

• Own the architecture, technical direction, and roadmap for the company's AI and autonomous-agent capabilities.
• Personally design, build, test, deploy, and support production AI agents and agentic workflows.
• Develop production agentic solutions, preferably using LangChain and LangGraph or comparable frameworks, including autonomous and multi-step workflows, tool use, orchestration, and enterprise integrations.
• Establish and implement approaches for agent evaluation, testing, tracing, monitoring, observability, reliability, and production support.
• Design and implement integrations between AI agents and enterprise applications, APIs, tools, databases, and governed enterprise data.
• Develop and implement Model Context Protocol (MCP) and appropriate integration patterns for connecting agents with enterprise systems, tools, and data.
• Build APIs, connectors, and integration components required to support AI and automation solutions.
• Partner directly with business stakeholders to understand workflows, business problems, and high-value use cases and translate them into practical AI solutions.
• Develop AI and automation solutions supporting areas such as research, R&D, patent analysis, accounting, and other enterprise business processes.
• Define reusable architecture, development patterns, and engineering standards for production AI solutions.
• Ensure AI solutions operate within established data, security, privacy, and AI governance requirements.
• Evaluate emerging AI technologies, frameworks, platforms, and architectural approaches and determine where they can provide meaningful business value.
• Work closely with the data function to ensure AI agents consume accurate, appropriately structured, governed enterprise data.
• Direct external resources or contractors when additional implementation capacity is required while retaining direct ownership of architecture, technical decisions, engineering, and delivery.

Minimum Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, or a related technical discipline.
• 7+ years of professional software engineering, application development, or related experience, including 3+ years focused on AI/ML, generative AI, or AI-enabled application development.
• Demonstrated experience personally designing, building, deploying, and supporting production AI agents with multi-step workflows, tool use, and orchestration.
• Demonstrated ability to own both the architecture and hands-on engineering of AI solutions, including defining technical direction, evaluating technologies and architectural approaches, and personally designing, building, deploying, and supporting production AI agents.
• This is an individual contributor role without a broader AI engineering team, requiring someone equally comfortable making architectural decisions and executing the engineering work.
• Experience with LangChain and LangGraph is strongly preferred; comparable production agent frameworks are acceptable.
• Strong proficiency in Python and modern software engineering practices.
• Strong understanding of agent architecture, tool use, orchestration, APIs, enterprise integrations, and enterprise data access patterns.
• Experience integrating AI agents with enterprise applications, APIs, databases, data platforms, and business systems.
• Experience taking AI solutions through the complete lifecycle from architecture and development through testing, deployment, monitoring, reliability, and production support.
• Experience with production engineering practices including CI/CD, testing, monitoring, observability, tracing, performance, and reliability.
• Ability to evaluate emerging AI technologies, frameworks, and architectural approaches and make sound technical decisions based on business requirements, scalability, maintainability, security, and production viability.
• Ability to work directly with business stakeholders to understand complex workflows and translate business needs into practical technical solutions.
• Ability to independently own complex AI initiatives from initial architecture through implementation and production operation.
• Must be located in the Detroit / Southeast Michigan area and able to work onsite 2–4 times per month, up to 1 day per week.

Preferred Qualifications

• Experience with LangSmith for tracing, evaluation, monitoring, and debugging production agentic applications.
• Experience implementing Model Context Protocol (MCP) and agent-to-tool or agent-to-system integration patterns.
• Background in data engineering, machine learning engineering, or enterprise data platforms, particularly where data quality and structure directly affect AI solution performance.
• Experience developing AI solutions that interact with enterprise systems such as Salesforce, ERP, financial, contract-management, research, or other business applications.
• Experience directing external engineering resources or implementation partners when additional implementation capacity is required while retaining direct architectural and engineering ownership.
• Success Profile AI agents and automations are reliable in production.
• Business teams can successfully adopt and build with AI.
• The enterprise AI platform scales securely and operates within governance standards.
• The multi-year AI roadmap is delivered and engineering standards are consistently adopted.
• AI engineering capability grows across IT and business teams .
• Work Arrangement This position is primarily remote but requires candidates to be located in the Detroit / Southeast Michigan area.
• The role requires in-person collaboration 2–4 times per month, up to 1 day per week, in the Detroit area.
• Compensation & Benefits Compensation depends on experience but is typically $184,000–$200,000/year, plus a 15% target annual bonus and RSUs targeted at 60% of annualized base salary.
• Benefits include medical, dental, and vision insurance, 401(k), paid time off, and other company-sponsored benefits.