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United States
Remote only
Not Available
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal - Software Engineer based in the United States.
This is a hands-on principal-level engineering role focused on building the next generation of AI-powered applications for supply chain and operations.
You’ll own full-stack development across the software lifecycle, from architecture and implementation through deployment, monitoring, and continuous improvement.
A major focus will be embedding AI capabilities such as LLMs, predictive insights, recommendations, conversational interfaces, and agentic workflows into production applications.
You’ll also work with knowledge graphs, ontologies, modern cloud platforms, and reusable AI tool interfaces to transform operational data into actionable decision-making solutions.
Beyond individual contribution, you’ll help shape technical direction, establish engineering standards, and mentor junior engineers and BI developers.
You’ll collaborate closely with technical leaders and business stakeholders to turn ambiguous, high-impact problems into scalable, production-ready products.
This remote opportunity is ideal for a highly experienced engineer who enjoys solving complex problems, leading through influence, and balancing hands-on development with technical mentorship.
Design, build, test, deploy, and maintain full-stack applications and services across the complete software development lifecycle.
Develop responsive front-end experiences and scalable back-end services deployed to cloud environments.
Monitor application performance, errors, latency, and usage while owning alerting, incident response, troubleshooting, and root-cause analysis.
Integrate AI capabilities into production applications, including natural-language queries, predictive insights, recommendations, conversational experiences, and intelligent decision-support features.
Integrate machine-learning models and LLM APIs into applications to enhance operational insights and business outcomes.
Build agentic workflows capable of triggering actions and updating records while incorporating appropriate human approval and audit logging.
Develop and expose reusable AI capabilities through MCP servers or equivalent tool interfaces that can be accessed by applications and agents.
Use knowledge graphs and ontologies to represent domain knowledge, support semantic search, and enable AI-powered reasoning over connected operational data.
Partner with junior engineers and BI developers to move AI and machine-learning concepts from experimentation into reliable, production-grade capabilities.
Establish and enforce coding standards, design patterns, engineering practices, and quality expectations across the team.
Conduct senior-level code reviews focused on correctness, performance, security, reliability, and maintainability.
Establish and improve CI/CD pipelines, automated testing practices, version-control workflows, and secure-by-default engineering processes.
Build reusable components, templates, and utilities that accelerate application development across the team.
Mentor and coach junior software engineers and BI developers while remaining actively involved in hands-on development.
Translate ambiguous business challenges into clear project plans, technical solutions, and shippable increments.
Lead application projects of moderate to high complexity and influence technical direction across the team.
Partner with BI leadership on application roadmaps and with business stakeholders to define requirements, priorities, and expected outcomes.
Bachelor’s degree in Computer Science, Software Engineering, or a related technical field from an accredited university or college.
At least 8 years of hands-on experience building and delivering full-stack applications to production.
Strong expertise across modern front-end and back-end technologies, with the ability to own applications end to end.
Demonstrated experience integrating machine-learning models, LLM APIs, and agentic workflows into production applications.
Experience building MCP servers or comparable tool interfaces that applications and AI agents can use in production environments.
Experience modeling domain knowledge through knowledge graphs and ontologies to support semantic search, AI grounding, and reasoning over connected data.
Familiarity with cloud application hosting and modern data platforms such as Databricks, AWS, Snowflake, or comparable technologies.
Strong engineering fundamentals, including Git, CI/CD, automated testing, code review, application security, and secure-by-default practices.
Ability to debug complex issues across the full technology stack, including front-end applications, APIs, databases, and integrations.
Strong problem-solving skills and the ability to break ambiguous business challenges into clear, practical, and deliverable increments.
Ability to evaluate technical trade-offs such as build versus buy, batch versus real-time processing, and speed versus reliability.
Strong communication skills, with the ability to explain technical concepts and trade-offs to both technical and non-technical audiences.
Demonstrated ability to collaborate effectively with BI developers, data and AI/ML engineers, and business stakeholders.
Leadership skills based on influence, technical expertise, evidence, and example rather than formal authority.
Player-coach mindset, balancing hands-on engineering with mentoring, code review, and technical leadership.
Strong commitment to application reliability, security, testing, and long-term maintainability.
Demonstrated ownership of applications from design and development through deployment, monitoring, and continuous improvement.
Experience in supply chain, manufacturing, maintenance, or other operational domains is a strong plus.
A Master’s degree in a related technical field is preferred.
Must be legally authorized to work in the United States.
Base salary range of $152,000–$202,000 per year, with actual compensation influenced by experience, education, skills, and other relevant factors.
Eligibility for an annual discretionary bonus and/or commission opportunity based on the applicable compensation plan.
Medical, dental, vision, and prescription drug coverage.
Access to health and wellness resources, including a Health Coach.
Employee Assistance Program with 24/7 confidential assessment, counseling, and referral services.
401(k) savings plan with company matching contributions and additional retirement contributions.
Access to retirement planning resources and financial consultants.
Tuition assistance.
Adoption assistance.
Paid parental leave.
Disability insurance.
Life insurance.
Paid time off for vacation or illness.
Remote work arrangement.
Professional development opportunities and exposure to complex, high-impact engineering challenges.
New Hire Orientation requires in-person attendance on Day 1.
No relocation assistance is provided.