Solutions Engineer

Summary

Oden Technologies is a manufacturing AI company that combines large-scale data processing with advanced AI and ML algorithms to help manufacturing operations improve efficiency and productivity. The Solutions Engineer delivers technical post-sales work, including designing integrations, deploying AI/ML solutions, troubleshooting data and system issues, supporting enterprise customers, and translating customer needs into product improvements.

Responsibilities

• Serve as the primary technical resource on assigned accounts — from discovery and solution design through deployment, integration, and ongoing technical support
• Work in close partnership with the Solutions Manager and Customer Success Engineers, ensuring technical and relationship responsibilities are clearly covered across the team
• Build trusted relationships with customer technical leads, IT teams, and manufacturing operations stakeholders — becoming the go-to for technical questions, troubleshooting, and integration guidance
• Proactively surface technical risks and blockers early, and pull in the right internal expertise when needed to keep deployments on track
• Collaborate with Sales, Data Science, and Product Engineering to understand customer use cases, data integration requirements, and technical constraints given the different data models across customers and Oden
• Design and implement technical solutions that integrate relevant data sources to Oden’s cloud endpoints, including system configurations, data architecture, and integration requirements. Have a strong understanding of the correctness and performance (latency/uptime) for every deployed integration. These are complex distributed systems and being able to understand their interactions and points of failure is critical
• Oversee integration with existing manufacturing systems including ERP, MES, and QMS platforms; manage dependencies, sequencing, and technical risks across systems
• Develop, maintain, and improve connector libraries that interface Oden with common manufacturing and enterprise systems — building reusable tooling that makes future deployments faster and more repeatable. Collaborate with the product and platform engineering team to integrate these libraries into the product
• Work with Data Science to design the solution for the customer problem, including the use of AI and ML models. Lead the technical implementation of Oden solution — configuring and customising the platform, building models and detectors, and combining them with alerts and recommendations to align with customer workflows, processes, and business rules and drive value
• Actively develop implementation planning on your accounts — scope, configurations, timelines, and milestones — in collaboration with the Solutions Manager or Customer Success Engineer coordinating the account and delivering results in a timely manner
• Serve as a subject matter expert on Oden’s architecture, APIs, and data models — and stay current as the platform evolves
• Troubleshoot technical issues across networking, data pipelines, QA, and system configurations, both remotely and on-site. Have a demonstrated ability to understand data and common issues with data and integrations that impact the solution, and be able to independently triage issues and deploy fixes/solutions
• Translate field observations and product gaps into structured, actionable feedback for Product and Engineering; you are one of the clearest signals the product team has into what is actually happening at customer sites
• Provide guidance to customers and internal teams on implementation best practices, integration patterns, and technical methodologies
• Work directly with the product engineering team to setup requirements, and drive updates and improvements to the product capabilities
• Develop and maintain integration documentation to support repeatable, scalable deployments
• Develop and maintain solution design and implementation documentation to support maintenance, and replicability
• Continuously update documentation based on customer feedback, product changes, and lessons learned across the account base

Skills

• • 4+ years of experience in a technical customer-facing role — Solutions Engineer, Forward Deployed Engineer, Implementation Engineer, Technical Consultant, or similar — supporting enterprise SaaS deployments or digital transformation projects
• • Programming experience: Python, Golang or equivalent, SQL, REST APIs, familiarity with Bash and terminal-based workflows, AI-powered coding assistants
• • Strong experience with large datasets - management, processing, analysis - using off the shelf analytical tools, including AI tools
• • Experience with distributed systems, middleware and integration toolsets, Windows and Linux operating systems, enterprise networking and troubleshooting, and deploying and maintaining remote applications. Have strong experience understanding and debugging issues with performance, correctness, and reliability of these integrations. Comfortable with Google Cloud
• • Technically strong and comfortable working independently on complex integration problems — you can go deep on a technical challenge, work through it methodically, and communicate progress clearly to both technical and non-technical stakeholders
• • Strong written communication skills: technical documentation, customer-facing summaries, and internal knowledge sharing
• • Strong project management and self-organisation skills; able to manage multiple accounts and priorities simultaneously
• • Comfortable in ambiguous, fast-moving environments where requirements shift and no two accounts look the same
• • Willingness to travel to customer sites ~25–40% depending on deployment phase
• • Hold a US drivers license
• • Based in NYC metro, Atlanta, Chicago, Austin, Boston, Minneapolis
• At this time, we cannot offer visa sponsorship. Candidates must be authorized to work in the United States without current or future employer sponsorship
• • Direct experience working in manufacturing operations, industrial engineering, reliability, or OT — having worked on or alongside a production floor
• • Customer-facing exposure to manufacturing, field management, construction, or other operational technology environments - ability to be credible in industrial environments
• • Familiarity with OEE, fault analysis, predictive analytics, or production AI use cases in a manufacturing context
• • Experience with data pipeline tooling (Airflow, Databricks, or similar) and BI or dashboard platforms
• • Prior experience at a growth-stage industrial technology or SaaS company (30–200 people)
• • Experience contributing to product feedback loops and roadmap prioritisation in a customer-facing role

Qualifications

Must Haves

• • 4+ years of experience in a technical customer-facing role — Solutions Engineer, Forward Deployed Engineer, Implementation Engineer, Technical Consultant, or similar — supporting enterprise SaaS deployments or digital transformation projects
• • Programming experience: Python, Golang or equivalent, SQL, REST APIs, familiarity with Bash and terminal-based workflows, AI-powered coding assistants
• • Strong experience with large datasets - management, processing, analysis - using off the shelf analytical tools, including AI tools
• • Experience with distributed systems, middleware and integration toolsets, Windows and Linux operating systems, enterprise networking and troubleshooting, and deploying and maintaining remote applications. Have strong experience understanding and debugging issues with performance, correctness, and reliability of these integrations. Comfortable with Google Cloud
• • Technically strong and comfortable working independently on complex integration problems — you can go deep on a technical challenge, work through it methodically, and communicate progress clearly to both technical and non-technical stakeholders
• • Strong written communication skills: technical documentation, customer-facing summaries, and internal knowledge sharing
• • Strong project management and self-organisation skills; able to manage multiple accounts and priorities simultaneously
• • Comfortable in ambiguous, fast-moving environments where requirements shift and no two accounts look the same
• • Willingness to travel to customer sites ~25–40% depending on deployment phase
• • Hold a US drivers license
• • Based in NYC metro, Atlanta, Chicago, Austin, Boston, Minneapolis
• At this time, we cannot offer visa sponsorship. Candidates must be authorized to work in the United States without current or future employer sponsorship

Nice to Haves

• • Direct experience working in manufacturing operations, industrial engineering, reliability, or OT — having worked on or alongside a production floor
• • Customer-facing exposure to manufacturing, field management, construction, or other operational technology environments - ability to be credible in industrial environments
• • Familiarity with OEE, fault analysis, predictive analytics, or production AI use cases in a manufacturing context
• • Experience with data pipeline tooling (Airflow, Databricks, or similar) and BI or dashboard platforms
• • Prior experience at a growth-stage industrial technology or SaaS company (30–200 people)
• • Experience contributing to product feedback loops and roadmap prioritisation in a customer-facing role

Benefits

• Equity
• Benefits
• Remote work arrangement
• Career development with personalized pathways for growth and advancement