Articul8 AI

Engineering Manager

• Write clean, scalable, and performant code using React, TypeScript, and modern UI frameworks.
• Review code, drive architecture discussions, and help resolve complex technical challenges.
• Contribute directly to building reusable UI components, design systems, and interactive GenAI experiences.
• Lead and mentor a team of frontend engineers, balancing technical contributions with people management.
• Foster a culture of collaboration, accountability, and technical excellence.
• Partner with Product and Design to translate vision into concrete engineering deliverables.
• Define the frontend engineering roadmap and set technical best practices (testing, CI/CD, accessibility, performance).
• Guide adoption of modern developer tooling (e.g., Replit, Vite, Webpack, GraphQL/REST APIs) to increase velocity.
• Stay current with emerging frontend/GenAI technologies and evaluate their fit for the platform.
• Ensure reliable, secure, and enterprise-ready deployments of frontend applications.
• Drive metrics for code quality, performance, and user satisfaction.
• Champion accessibility, responsive design, and usability across devices.
• Embrace experimentation—prototype rapidly, fail fast, and iterate with purpose.
• Be hands-on in high-impact deployments and customer environments.

Software Engineering Manager, Applications/Frontend

Solutions Engineer

• Design and deploy scalable architectures for manufacturing use cases including industrial operations that include SCADA/HMI, EDA, IoT, Machine Learning, AI, and advanced analytics.
• Lead technical workshops, prototype solutions, and oversee platform deployment and optimization.
• Collaborate with product and engineering teams to incorporate customer feedback into the product roadmap.
• Advise customers on Articul8 product adoption strategies with a focus on differentiating capability, security, cost, and operational efficiency.
• Architect and tune Kubernetes-based and containerized infrastructure leveraging cloud platforms (AWS, Azure, GCP, or on-premises) to ensure infrastructure excellence.
• Develop reusable solution templates and document best practices.
• Partner with sales and business development to drive cloud adoption and align solutions with industry trends.
• Continuously monitor and improve deployed solutions for performance and scalability.
• Communicate technical concepts clearly to diverse audiences and advocate for customer needs internally.
• Stay current with emerging manufacturing and cloud technologies to inform strategy and ability to support other industry verticals when required.
• Guide product roadmap by driving feedback and market insights into solution strategy and product development in complex enterprise environments.
• Serve as a senior technical partner merging manufacturing domain expertise, cloud architecture proficiency, and customer success engagement.

Industries Solutions Architect – Manufacturing & Industrial

SDET

• Design, develop, and maintain advanced test automation frameworks that incorporate chaos engineering principles
• Create and execute chaos experiments that simulate various failure modes and edge cases in our distributed systems
• Implement monitoring solutions that effectively track system performance, resilience, and failure recovery
• Establish observability practices that provide deep insights into system behavior during chaos experiments
• Collaborate with development teams to build resilience into our applications from the ground up
• Develop metrics and dashboards to visualize system reliability and the impact of chaos experiments
• Lead post-mortem analyses to identify system weaknesses discovered through chaos testing
• Integrate chaos testing into CI/CD pipelines to validate system resilience continuously
• Mentor engineers through code reviews, technical sessions, and hands-on guidance in test automation, chaos engineering, and monitoring best practices
• Contribute to the company's overall testing strategy and quality assurance practices
• Work on resilience and reliability of AI-driven systems at scale as part of the Quality Engineering team

Senior Software Development Engineer in Test, SDET, Chaos Engineering Specialist

Machine Learning Engineer

• Design, develop, and deploy AI/ML models ranging from traditional ML regression algorithms to transformer-based architectures.
• Train, fine-tune, and optimize deep learning and LLM-based solutions.
• Engage with customers to understand their needs and transform them into actionable tasks for developing new functionalities within the Articul8 platform.
• Collaborate with researchers, software engineers, and product teams to integrate new AI capabilities into our applications.
• Implement and evaluate state-of-the-art automated testing and metrics to improve model accuracy and efficiency.
• Optimize models for both cloud and on-premises environments to ensure low latency and high availability.
• Develop APIs and micro-services to serve AI models in production.
• Stay current with the latest AI models, research, and best practices.
• Ensure ethical AI practices, data privacy, and security compliance.

Senior/Staff AI/ML Engineer

• Write clean, scalable, and performant code using React, TypeScript, and modern UI frameworks.
• Review code, drive architecture discussions, and help resolve complex technical challenges.
• Contribute to building reusable UI components, design systems, and interactive GenAI experiences.
• Lead and mentor a team of frontend engineers, balancing technical contributions with people management.
• Foster a culture of collaboration, accountability, and technical excellence.
• Partner with Product and Design to translate vision into engineering deliverables.
• Define the frontend engineering roadmap and set technical best practices (testing, CI/CD, accessibility, performance).
• Guide adoption of modern developer tooling (Replit, Vite, Webpack, GraphQL/REST APIs) to increase velocity.
• Stay current with emerging frontend/GenAI technologies and evaluate their fit for the platform.
• Ensure reliable, secure, and enterprise-ready deployments of frontend applications.
• Drive metrics for code quality, performance, and user satisfaction.
• Champion accessibility, responsive design, and usability across devices.
• Embrace experimentation—prototype rapidly, fail fast, and iterate.
• Be hands-on in high-impact deployments and customer environments.

Infrastructure Engineer

• Design, develop, test, deploy, maintain, and improve cloud-based infrastructure focusing on high availability, low latency, and cost-effectiveness
• Develop automation scripts, tools, and frameworks to streamline deployment, monitoring, and maintenance processes
• Serve as subject matter expert in infrastructure when designing new products and introducing new technology
• Collaborate closely with engineering and research teams to integrate infrastructure components with product features
• Implement robust security measures to safeguard sensitive data and prevent vulnerabilities
• Analyze performance metrics, identify areas for optimization, and propose data-driven improvements
• Stay up-to-date with emerging trends, technologies, and methodologies and apply this knowledge to enhance infrastructure
• Participate in code reviews, contribute to open-source projects, and mentor junior engineers

• Design, develop, and maintain advanced test automation frameworks that incorporate chaos engineering principles
• Create and execute chaos experiments that simulate various failure modes and edge cases in our distributed systems
• Implement monitoring solutions that effectively track system performance, resilience, and failure recovery
• Establish observability practices that provide deep insights into system behavior during chaos experiments
• Collaborate with development teams to build resilience into our applications from the ground up
• Develop metrics and dashboards to visualize system reliability and the impact of chaos experiments
• Lead post-mortem analyses to identify system weaknesses discovered through chaos testing
• Integrate chaos testing into CI/CD pipelines to validate system resilience continuously
• Mentor engineers through code reviews, technical sessions, and hands-on guidance in test automation, chaos engineering, and monitoring best practices
• Contribute to the company's overall testing strategy and quality assurance practices

Senior Software Development Engineer in Test, Chaos Engineering Specialist

DevOps Engineer

• Architect and maintain scalable, highly available infrastructure for our GenAI platform
• Design and implement robust monitoring, alerting, and observability solutions to proactively ensure system health and performance
• Automate deployment, scaling, and management of our cloud-native infrastructure, reducing toil and improving efficiency
• Define, measure, and improve Service Level Objectives (SLOs) and Service Level Indicators (SLIs)
• Participate in on-call rotations and provide rapid response to production incidents
• Collaborate closely with development teams to build reliable, scalable, and efficient systems for complex AI workloads
• Lead incident response efforts, conduct thorough post-mortems, and champion continuous improvement initiatives
• Optimize infrastructure for performance, scalability, and cost-effectiveness—especially for high-demand AI workloads
• Implement and enforce security best practices across all systems and environments
• Create and maintain comprehensive documentation, including runbooks and knowledge base articles

Senior Site Reliability Engineer, SRE

AI Research Scientist

• Serve as the subject matter expert in various domains of GenAI research and development (data pipelines, training methodologies, reinforcement learning, multimodal AI, personalization, knowledge representation and retrieval).
• Play a technical leadership role in designing, developing, and scaling novel algorithms and models from research prototypes to production-ready systems.
• Partner with cross-functional teams to integrate cutting-edge research findings into products and maintain technological leadership.
• Monitor and analyze emerging trends in generative AI and share research contributions through publications at conferences and journals.

Senior/Staff AI Researcher

• Conduct cutting-edge research to advance the capabilities of GenAI systems; design, implement, and evaluate novel approaches to improve GenAI models.
• Work at the intersection of GenAI research and product development, taking research prototypes to production-ready systems.
• Serve as subject matter expert in GenAI domains including data pipelines; training methodologies (pre/mid/post-training) and optimization techniques; reinforcement learning for GenAI; multimodal AI (text, image, audio, video); personalization; knowledge representation and retrieval.
• Play a technical leadership role in designing, developing, and scaling novel algorithms and models.
• Partner with cross-functional teams to integrate research findings into products and maintain technological leadership.
• Monitor and analyze emerging trends in generative AI and share research via publications at conferences and journals.