About Viaduct
At Viaduct, we use patented AI to discover hidden patterns in complex time series data – so manufacturers and operators of connected equipment can deliver transformative business results from their data, fast. On our platform we deliver solutions across the equipment lifecycle, from manufacturing productivity, manufacturing quality, service operations and fleet management.
Who You Are
You are a thoughtful engineer. You understand the complexities of distributed systems and how to triage and solve issues that arise with them. You are a "doer" who thrives on the challenge of delivering high-stakes implementations in complex enterprise environments. You believe that successful software deployment requires a bridge between robust data engineering and cutting-edge AI. You are comfortable working directly with customers to understand their technical landscapes and ensure that software solutions are integrated, deployed, and delivering value quickly.
About the Role
As an Integration Engineer at Viaduct, your work is critical to our success. You are responsible for the "last mile" of our technology—ensuring seamless data flow from customer systems into our platform and deploying our AI solutions within enterprise contexts. You will own the technical implementation process, making key decisions on data integration and building the connectors that power our intelligence engine. A major focus of this role is the practical deployment of LLM and Agentic systems, ensuring they are configured, tested, and iterated upon to solve real-world manufacturing and operations challenges.
Key Responsibilities
- Enterprise Deployment: Lead the hands-on technical implementation and deployment of Viaduct’s software solutions within large-scale enterprise environments.
- Data Integration & Connectivity: Make critical data integration decisions and build robust connectors across a variety of data types and systems (SQL, NoSQL, APIs, etc.).
- Pipeline Engineering: Create and support batch, incremental, and real-time data pipelines to ensure high-quality data ingestion from client systems.
- AI Implementation: Set up and deploy LLM and agentic systems in practice. You will be responsible for prompt engineering, performance testing, and iterating on agent behavior to ensure reliability and accuracy.
- Standardization: Establish and automate validation and cleaning processes to ensure data quality across various client integrations.
- Customer Collaboration: Work directly with customers across a variety of contexts to troubleshoot technical hurdles and ensure successful solution adoption.
Position Details:
- Compensation: Competitive base salary, short-term incentive (annual bonus) and long-term incentive (long-term upside)
- Travel: 0-50% (with significant international travel component)
- Employment Type: Full Time
- Work site: Up to 100% work from home
- Team: Internal Efficiencies
Qualifications
- Implementation Experience: Proven track record of delivering software implementations at a large enterprise software company (e.g., Salesforce, ServiceNow, Oracle, C3 AI, Palantir) or a leading consulting firm (e.g., Accenture, Deloitte, McKinsey).
- Technical Proficiency: Very good at Python and ideally SQL.
- AI/LLM Experience: Direct experience setting up and deploying LLM-based systems and agentic frameworks in practical, real-world settings. You know how to test and iterate on prompt performance.
- Data Engineering Foundation: 4+ years of experience in data engineering or implementations, including experience with workflow schedulers (Airflow, Prefect, Argo, etc.) and distributed file systems (S3, HDFS, etc.).
- Infrastructure Knowledge: Experience with incremental or real-time processing (Delta Lake, Apache Hudi, Kafka, Spark Streaming).
- Scrappy Mindset: You have done a number of implementation projects across a variety of relevant contexts and value "getting it done" over theoretical perfection.
- Education: A degree in Computer Science or a related field is helpful, but we value a history of successful, scrappy implementation projects over fancy credentials or advanced degrees.
Security and Privacy Responsibilities
- Follow our policy and procedure documents related to security and privacy
- Follow the security and privacy guidelines in the Employee Handbook
- Participate in new hire and annual training for security and privacy
- Treat data security and privacy as one of your primary job responsibilities
- Report Security Incidents you discover as bugs
- Get approval from the Security Team before adding new 3rd party software to our codebase
- Explicitly consider security implications when doing PR reviews
Bonus
- Experience with Kubernetes
- Experience working with ML teams
- Contributor to open-source projects
- Experience in the Automotive or Manufacturing industry
Why Join Us? At Viaduct (now part of Sumitomo Rubber Industries), you will work at the intersection of industry-leading AI and global manufacturing. You’ll have the opportunity to take cutting-edge AI technology out of the lab and into the real world, creating immediate, transformative value for some of the largest manufacturers in the world.