We build digital platforms that help engineering and manufacturing teams turn operational data into trusted insights and faster decisions. Our solutions bring together data from multiple systems, standardize performance measures, provide dashboards and analytical drill-downs, and support alerts, investigation workflows, and AI-assisted decision support.

We are seeking an experienced R&D Software Engineer to provide hands-on technical leadership for this platform. This role combines full-stack software development with solution architecture, technology pathfinding, and production ownership. You will shape the technical direction, evaluate technology options, establish reusable engineering patterns, and lead complex capabilities from concept through reliable operation.

The ideal candidate is a strong software engineer and system thinker who can work across user experience, backend services, APIs, data integration, security, deployment, and operational reliability while guiding other engineers through clear, evidence-based technical decisions.

Responsibilities

Own the end-to-end solution architecture across web applications, backend services, APIs, data access, integrations, security, deployment, monitoring, and supportability.
Translate complex operational and business problems into scalable solution designs, technical roadmaps, implementation options, and clear engineering decisions.
Lead architecture and design reviews; document decisions, alternatives, trade-offs, risks, constraints, and migration considerations.
Evaluate emerging technologies, frameworks, integration approaches, and platform capabilities through focused prototypes and technical experiments; recommend whether to adopt, contain, or reject each option based on evidence.
Define technology evolution paths that balance near-term delivery with long-term scalability, maintainability, security, interoperability, and total cost of ownership.
Establish reusable reference architectures, API patterns, coding standards, integration contracts, component strategies, and engineering guardrails.
Design and develop production-grade user interfaces, backend services, business logic, data-access components, secure REST APIs, and system integrations.
Create stable, governed interfaces that reduce dependency on physical database structures and allow backend data models to evolve without disrupting consumers.
Deliver analytical and decision-support capabilities such as performance dashboards, drill-down analysis, alerts, investigation workflows, action tracking, and operational recommendations.
Integrate analytical, machine-learning, or generative-AI outputs into user-facing workflows with appropriate validation, human oversight, traceability, exception handling, and audit controls.
Own critical non-functional requirements including performance, scalability, availability, resilience, cybersecurity, maintainability, observability, and production support.
Lead technical problem solving for high-impact application, integration, data-access, performance, and production issues across the full technology stack.
Break complex initiatives into incremental, testable, and releasable capabilities, and guide implementation through design, development, testing, deployment, and operation.
Mentor engineers through design guidance, code reviews, debugging, architecture discussions, and reusable engineering practices.
Partner with product, data, user-experience, quality, operations, security, and domain specialists to align technical solutions with user value and operational constraints.
Remain hands-on in software development, prototyping, integration, testing, and critical-path implementation while providing technical leadership across the team.
Create and maintain architecture diagrams, solution designs, API specifications, decision records, technical standards, deployment guidance, and operational documentation.

Qualifications

Bachelor's or Master's degree in Computer Science, Software Engineering, Computer Engineering, Information Technology, or a related technical field.
More than 8 years of professional software engineering experience, including ownership of complex, production-grade systems or platforms.
Demonstrated experience in software architecture, solution design, technical decision-making, and leading implementations across multiple application layers.
Strong object-oriented programming, abstraction, systems thinking, problem-solving, and software design skills.
Hands-on backend development experience using C# and .NET, or a comparable enterprise application stack.
Hands-on frontend development experience using TypeScript or JavaScript and a modern framework such as Angular or React.
Strong experience designing versioned REST APIs, service boundaries, integration contracts, and application interfaces.
Experience with relational databases, SQL, data modeling, query optimization, data validation, and data-intensive application design.
Experience applying architecture and design patterns for modularity, scalability, resilience, security, testability, and maintainability.
Experience with automated testing, source control, code review, continuous integration and delivery, production monitoring, and incident troubleshooting.
Ability to evaluate technology options, build prototypes, compare trade-offs, identify risks, and present a clear recommendation to technical and business stakeholders.
Strong written and verbal communication skills, including the ability to explain complex technical decisions in clear business and engineering language.
Proven ability to influence technical direction, mentor engineers, and collaborate effectively with distributed cross-functional teams.

Preferred Qualifications:

Experience architecting manufacturing, industrial, operational analytics, business intelligence, or enterprise workflow platforms.
Experience building dashboards, data visualizations, alerting solutions, investigation workflows, or analytical drill-down experiences.
Experience with cloud platforms, containerization, infrastructure automation, scalable deployment patterns, distributed systems, and observability tooling.
Experience with semantic models, governed data products, event-driven integration, data platforms, or cloud data warehouses.
Experience integrating machine-learning or generative-AI services into production software with validation, human oversight, and traceability.
Experience planning platform modernization, technology migration, incremental replacement, or coexistence between legacy and modern systems.
Familiarity with manufacturing concepts such as yield, cycle time, throughput, downtime, work in progress, process routing, stations, retest, and production constraints.

What Success Looks Like:

A coherent platform architecture and technology roadmap that support current delivery while reducing future redesign and integration risk.
Clear, evidence-based technology decisions supported by prototypes, trade-off analysis, and documented architecture rationale.
Reusable APIs, components, reference patterns, and engineering standards that improve delivery speed and consistency.
Reliable, secure, maintainable, and observable software capabilities that shorten the path from operational data to action.
Stronger team capability through practical mentoring, rigorous design reviews, and improved engineering discipline.
Progression from reporting and analytics toward explainable, accountable, and AI-assisted decision support without compromising quality or governance.

R&D Software Engineer - Full Stack & Solution Architecture