Solution Architect, Industrial Technology Pre-Sales (Remote)
Symphonyai Enterprise IT, New York, NY, United States
Solution Architect, Industrial Technology Pre-Sales (Remote)
SymphonyAI Industrial is a global leader in Industrial AI, enabling manufacturers and asset-intensive enterprises to transform fragmented IT, OT, and edge data into real-time, contextual intelligence that improves uptime, throughput, and operational efficiency. Our platform is built on Vertical AI - domain-aware models, ontologies, and knowledge graphs that understand industrial operations from day one. We are seeking a Solution Architect to join our customer applications team and play a defining role in shaping the future of our industrial AI platform. This role is for a senior solution architect with a deep curiosity for how systems really work - someone who enjoys reverse-engineering complex platforms, challenging assumptions, and designing forward-looking architectures while staying hands-on and closely connected to engineering teams. What You Will Do
Collaborate with clients and our partners to understand their business needs, challenges, and objectives, proposing tailored AI solutions that deliver measurable value. Recommend engineered features and AI models for specific industrial and/or supply chain applications while identifying required sensors/signals and other datasets. Engage with product development, product management, software engineering, data science, and delivery teams to develop high-value AI products and solutions. Provide critical inputs to the conceptual and detailed design of dashboards and front-end applications for industrial and/or supply chain use cases. Support clients with domain expertise for data analysis, requirements translation, problem definition, root cause analysis, sales/engineering training and business case/ROI analysis. Ensure successful customer delivery, value tracking, and demonstration of ROI for implemented AI solutions. What You Will Bring To SymphonyAI
Strong engineering domain expertise in one or more industrial verticals such as Power Generation, Oil & Gas, Metals, Mining, Chemicals, CPG, manufacturing or similar sectors. Deep understanding of industrial assets (e.g., turbines, compressors, pumps, heat exchangers, motors) and their failure modes, or industrial processes (e.g., refining, smelting, chemical reactors, food processing) from a process monitoring and optimization perspective. Hands-on expertise in supply chain domains, with the ability to contribute directly to the definition and build of data-driven supply chain solutions. Demonstrated experience deriving actionable insights from industrial data and architecting AI-driven solutions for real-world industrial challenges. Proven ability to engage with clients, understand their unique needs, and communicate technical solutions effectively to both technical and business audiences. Strong collaboration skills, with experience working in cross-functional, agile teams spanning product, engineering, and data science. Capability to develop technically rigorous training materials and deliver hands-on training for both engineering and sales audiences. Technical mentorship experience, fostering growth and best practices within engineering teams. Self-motivated, adaptable, and able to innovate quickly in a dynamic environment. Requirements/Qualifications
Bachelor's or Master's degree in a quantitative or engineering discipline. 8+ years of experience in industrial data analysis and AI/ML-based solution development for industrial customers. Software development experience in object oriented language. Experience engaging and collaborating with US and European clients, demonstrating excellent communication and cultural adaptability. Experience working across multidisciplinary teams covering product development, data science, software engineering, and delivery. Excellent written and verbal communication skills. Willingness to travel as required to support client success. Preferred
Experience with Python-based data analysis tools, including Scikit-learn, NumPy, Pandas, and generative AI-based tools. Skilled with data visualization libraries such as Matplotlib, Plotly, and Seaborn.
SymphonyAI Industrial is a global leader in Industrial AI, enabling manufacturers and asset-intensive enterprises to transform fragmented IT, OT, and edge data into real-time, contextual intelligence that improves uptime, throughput, and operational efficiency. Our platform is built on Vertical AI - domain-aware models, ontologies, and knowledge graphs that understand industrial operations from day one. We are seeking a Solution Architect to join our customer applications team and play a defining role in shaping the future of our industrial AI platform. This role is for a senior solution architect with a deep curiosity for how systems really work - someone who enjoys reverse-engineering complex platforms, challenging assumptions, and designing forward-looking architectures while staying hands-on and closely connected to engineering teams. What You Will Do
Collaborate with clients and our partners to understand their business needs, challenges, and objectives, proposing tailored AI solutions that deliver measurable value. Recommend engineered features and AI models for specific industrial and/or supply chain applications while identifying required sensors/signals and other datasets. Engage with product development, product management, software engineering, data science, and delivery teams to develop high-value AI products and solutions. Provide critical inputs to the conceptual and detailed design of dashboards and front-end applications for industrial and/or supply chain use cases. Support clients with domain expertise for data analysis, requirements translation, problem definition, root cause analysis, sales/engineering training and business case/ROI analysis. Ensure successful customer delivery, value tracking, and demonstration of ROI for implemented AI solutions. What You Will Bring To SymphonyAI
Strong engineering domain expertise in one or more industrial verticals such as Power Generation, Oil & Gas, Metals, Mining, Chemicals, CPG, manufacturing or similar sectors. Deep understanding of industrial assets (e.g., turbines, compressors, pumps, heat exchangers, motors) and their failure modes, or industrial processes (e.g., refining, smelting, chemical reactors, food processing) from a process monitoring and optimization perspective. Hands-on expertise in supply chain domains, with the ability to contribute directly to the definition and build of data-driven supply chain solutions. Demonstrated experience deriving actionable insights from industrial data and architecting AI-driven solutions for real-world industrial challenges. Proven ability to engage with clients, understand their unique needs, and communicate technical solutions effectively to both technical and business audiences. Strong collaboration skills, with experience working in cross-functional, agile teams spanning product, engineering, and data science. Capability to develop technically rigorous training materials and deliver hands-on training for both engineering and sales audiences. Technical mentorship experience, fostering growth and best practices within engineering teams. Self-motivated, adaptable, and able to innovate quickly in a dynamic environment. Requirements/Qualifications
Bachelor's or Master's degree in a quantitative or engineering discipline. 8+ years of experience in industrial data analysis and AI/ML-based solution development for industrial customers. Software development experience in object oriented language. Experience engaging and collaborating with US and European clients, demonstrating excellent communication and cultural adaptability. Experience working across multidisciplinary teams covering product development, data science, software engineering, and delivery. Excellent written and verbal communication skills. Willingness to travel as required to support client success. Preferred
Experience with Python-based data analysis tools, including Scikit-learn, NumPy, Pandas, and generative AI-based tools. Skilled with data visualization libraries such as Matplotlib, Plotly, and Seaborn.