Staff Software Engineer

Description

The company builds software for global manufacturing, with a focus on vision-as-a-service, automation and AI enablement.

Its teams work across cloud platforms, plant-floor systems, camera-based inspection with computer vision, data platforms and AI-assisted engineering, including agentic workflows that help people work more safely and efficiently.

This Staff Software Engineer role owns major parts of a complex, production-critical platform with a high degree of autonomy. You will ramp up fast and work across the full lifecycle: requirements, design, testing, deployment, observability and continuous improvement.

You will coordinate across teams, line up technical dependencies and delivery plans, and help teams make and carry out sound decisions in ambiguous situations. You will have real influence over technical direction and the engineering practices used to evolve the platform.

The platform spans Python and FastAPI services, React and TypeScript front ends, Java and Spring Boot services, event-driven components, cloud infrastructure, data stores, security controls and manufacturing-system integrations. It ships through automated CI/CD pipelines on GitHub Actions, Azure and GitOps tooling.

You will also contribute to edge-to-cloud computer-vision work, such as in-plant monitoring, where cameras, plant infrastructure, machine-learning inference, operational services and user workflows must work reliably together.

The role mixes architecture with hands-on coding. You will set engineering direction, mentor engineers, work with manufacturing and product leaders, and deliver scalable solutions that run reliably in real plants. Practical machine-learning skill, including fine-tuning models and running them in production for inference, is valued.

Responsibilities

• Lead the architecture and delivery of scalable software used by manufacturing teams at several plants.
• Turn business and operational needs into clear technical requirements, service boundaries, interface contracts and delivery plans.
• Design, build, test and run production services in Python and FastAPI, React and TypeScript, Java and Spring Boot, and modern cloud technology.
• Build event-driven workflows that take in, normalize, store and distribute operational data and alerts.
• Set up reliable links to manufacturing, workforce, equipment, analytics and enterprise systems using well-defined APIs and messaging.
• Design data models and platform solutions across relational, graph and other suitable databases, plus caching, object storage and metrics platforms.
• Build secure software with authentication, authorization, plant-level access control, secrets management and defense in depth.
• Raise platform reliability through observability, health monitoring, performance work, automated testing, incident reviews and operational readiness.
• Lead practices for highly automated CI/CD, infrastructure automation, containerized deployment and environment promotion using GitHub, Azure and GitOps.
• Evolve shared platform capabilities so several manufacturing products can reuse common services, user experiences and operating patterns.
• Help connect plant-edge applications, cameras, machine-learning inference, cloud services, alerts and operator workflows in in-plant computer-vision solutions.
• Apply AI thoughtfully to engineering and plant operations, including AI-assisted development, intelligent automation and agentic capabilities that work through governed tools and services.
• Help run machine-learning workflows: fine-tune models, productionize them for reliable inference, and set up dependable evaluation, deployment, monitoring and lifecycle practices.
• Assess emerging technologies and turn promising ones into secure, maintainable prototypes and production solutions.
• Weigh delivery speed, maintainability, performance, security, cost and operational complexity when choosing architecture, and keep teams aligned.
• Give technical leadership across teams: explain decisions, align stakeholders, promote common practices and mentor engineers.
• Take part in technical planning, design reviews, code reviews, troubleshooting and other duties as assigned.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, Software Engineering or a related field.
• 8+ years of professional software engineering experience, including substantial production delivery.
• Deep experience designing distributed applications, microservices, APIs and event-driven systems.
• Strong professional experience with Python and modern backend frameworks such as FastAPI.
• Strong professional experience with React, TypeScript and modern frontend application development.
• Familiarity with Java and Spring Boot services in distributed enterprise platforms.
• Experience with data models and databases, including relational, graph and other suitable technologies such as PostgreSQL.
• Experience with modern cloud and container technologies such as Azure, Docker and Kubernetes (K8s), plus infrastructure automation and comparable DevOps practices.
• Experience building secure applications with identity, authentication, authorization, role-based access, secrets and secure service-to-service communication.
• Experience with automated testing, CI/CD pipelines, GitHub Actions or comparable tools, source control and production release practices.
• Experience with observability: structured logging, metrics, tracing, health checks, alerting and operational dashboards.
• Experience designing and supporting integrations with enterprise or industrial systems using APIs, messaging or event streaming.
• Ability to analyze complex systems, balance competing needs and make decisions that protect long-term platform health.
• Ability to explain technical concepts clearly to engineers, product leaders, manufacturing partners and other stakeholders.
• Willingness to travel periodically for collaboration, plant deployments, production readiness or other business needs.
• Ability to work effectively in a close, cross-functional team.
• Preferred: Leading architecture and technical strategy for a platform used across several products, sites or business units.
• Preferred: Delivering software for manufacturing, industrial automation, automotive, robotics, computer vision or other operational environments.
• Preferred: Plant-edge computing, industrial cameras, device health, telemetry or edge-to-cloud architectures.
• Preferred: Integrating systems with different ownership models, data contracts, release cycles and availability requirements.
• Preferred: Azure services such as Event Hubs, managed databases, object storage, Key Vault, managed identity or equivalent cloud services.
• Preferred: Redis or similar caching and real-time communication technologies.
• Preferred: Infrastructure as code, Helm, GitOps, Argo CD or comparable deployment automation.
• Preferred: AI-assisted software engineering across design, implementation, testing, debugging, documentation and continuous improvement, including large-language-model tools, retrieval-augmented generation, intelligent automation, agentic systems or governed AI integrations.
• Preferred: Fine-tuning machine-learning models and productionizing them for reliable inference, including evaluation, deployment, monitoring and lifecycle management.
• Preferred: Familiarity with machine-learning or computer-vision systems and the software interfaces needed to operate them reliably, without deep model-development specialization.
• Preferred: Experience evolving shared frontend and backend capabilities across multiple teams.
• Preferred: Experience with data federation, graph-based models, domain ownership or event-driven data synchronization.
• Preferred: Proven ability to develop, inspire and motivate engineers through technical leadership and mentorship, fostering collaboration across organizational and functional boundaries.
• Preferred: Strategic perspective combined with willingness to work hands-on, take smart risks and champion change with sound judgment.
• Preferred: Integrity, accountability, initiative and ownership from concept through production operation.
• Preferred: Strong problem-solving, written and verbal communication and stakeholder-management skills.
• Preferred: Curiosity and ongoing learning in software engineering, cloud platforms, manufacturing technology and artificial intelligence.

Conditions

The company does not provide immigration sponsorship for this role, so do not apply if you will need company immigration sponsorship now or in the future. This covers direct sponsorship, naming the company as employer of record on a government form, and any work authorization that requires a written submission or other company immigration support, such as H-1B, OPT, STEM OPT, CPT, TN or J-1.

This role is hybrid: you are expected to report to a specific location at least 3 times a week, or at the frequency set by your manager.

Relocation benefits are available for candidates who qualify under company policy.

Selected candidates may need to complete a role-related assessment and/or a pre-employment screening before starting.

The company is committed to a workplace free of unlawful discrimination that also fosters inclusion and belonging.

Benefits

• Support for your well-being at work and at home starts on day one. Total Rewards resources describe the full rewards package.