Software Engineer, Project, AI Platforms

Accountabilities:

Design, develop, and maintain platform services, software development kits (SDKs), and APIs that enable product teams to integrate AI capabilities into industrial software applications.
Build and support AI-powered features, including intelligent assistants, automated content generation, and diagnostic tools across multiple software platforms.
Develop and maintain Model Context Protocol (MCP) servers and tool interfaces, providing AI agents with secure and governed access to product environments, build systems, testing infrastructure, and telemetry.
Create and maintain AI evaluation frameworks, test suites, and regression gates to measure the quality, safety, performance, latency, and cost of AI-powered features before deployment.
Take ownership of subsystem architecture and development throughout the entire software lifecycle, from technical design and implementation to testing, deployment, and production support.
Establish and maintain observability standards, performance benchmarks, and operational requirements to ensure platform reliability and scalability.
Collaborate with product engineering teams, software architects, and security specialists to ensure AI integrations comply with operational technology and industrial control system (OT/ICS) requirements.
Apply appropriate security measures covering intellectual property protection, binary signing, data boundaries, and secure AI deployment practices.
Research, prototype, and evaluate emerging AI models, large language models (LLMs), and agent architectures, transforming successful experiments into reliable and reusable platform capabilities.
Improve internal AI-assisted software development workflows by optimizing coding agents, development tools, automated testing, and evaluation processes.
Share technical knowledge, best practices, and successful AI engineering approaches across multidisciplinary development teams.
Requirements:
Bachelor's degree or equivalent relevant professional experience is required.
A degree in Computer Science, Software Engineering, Electrical Engineering, or a related technical discipline is preferred.
Typically, at least 8 years of experience in a professional software product development environment.
Strong experience building, testing, and deploying production-grade software using Python, C#, or C++.
Demonstrated ability to design and develop scalable services, APIs, or platform components that other engineering teams can integrate into their products.
Practical experience using AI coding assistants, development agents, and LLM APIs as part of everyday software engineering workflows.
Familiarity with cloud technologies, particularly Microsoft Azure, containerized environments, and continuous integration and continuous delivery (CI/CD) pipelines.
Experience developing and evaluating LLM-powered applications, including tool calling, retrieval-augmented generation, agent frameworks, and automated evaluation strategies for non-deterministic systems.
Knowledge of Model Context Protocol (MCP) and experience developing integrations that allow AI agents to interact with external tools and systems is an advantage.
Understanding of industrial automation technologies and concepts, such as programmable logic controllers (PLCs), OPC UA, and industrial engineering or design software, is preferred.
Experience applying secure software development principles to applications incorporating LLMs, AI agents, and automated decision-making capabilities.
Strong analytical and problem-solving abilities, with the capacity to translate complex technical challenges into practical and maintainable solutions.
Excellent written and verbal communication skills, with the ability to collaborate effectively across engineering, product management, architecture, and security teams.
Adaptability, curiosity, and a continuous learning mindset, particularly regarding rapidly evolving AI technologies and software engineering practices.
Compensation and seniority level will be determined by relevant professional experience, technical expertise, and qualifications.
Benefits:
Competitive annual base salary: $139,680–$176,600, depending on skills, qualifications, education, and professional experience.
Annual performance bonus: Target bonus equivalent to 8% of base salary.
Comprehensive health insurance, including medical, dental, and vision coverage.
401(k) retirement savings plan.
Paid time off to support personal well-being and work-life balance.
Parental and caregiver leave programs.
Flexible working schedules, allowing employees to coordinate their professional responsibilities with their personal commitments.
Remote working opportunities.
Exposure to cutting-edge AI technologies, industrial automation platforms, and innovative software engineering projects.
Opportunities to collaborate with experienced engineering, product, architecture, and security professionals.
A diverse, inclusive, and supportive working environment that encourages innovation, professional development, and continuous learning.