Senior embedded engineer developing safety - critical ECU firmware for Hexagon Mining’s digital mining and vehicle - control technologies. Designing, testing, and commissioning embedded systems.
About the role
- Senior Software Engineer building interfaces, REST APIs, and tooling for Introhive’s AI-powered relationship intelligence platform. Optimizing ML platform scalability and delivering production-ready enterprise features.
Responsibilities
- Extend existing enterprise applications with new user interfaces and RESTful APIs that surface AI-powered capabilities to customers
- Partner with ML engineers, UX designers, and product managers to translate model outputs and user requirements into production-ready features
- Own features end to end, from database and API design through front-end implementation and deployment
- Identify opportunities to optimize system architecture, performance, and scalability across the ML platform
- Design and build internal tooling for deploying, testing, monitoring, and operating ML models and pipelines
- Champion engineering best practices, including code reviews, testing strategies, documentation, and mentorship of junior engineers
- Work with quality engineering to improve automated testing processes and application reliability
- Contribute to technical roadmap discussions and translate business goals into architectural decisions
- Work independently and collaboratively within the team
Requirements
- University degree or equivalent in Computer Science, Software Engineering, or a related field
- 7+ years of professional software development experience
- Strong proficiency in at least one back-end language; Ruby/Rails experience is a plus; Python is used
- Ability and desire to learn new languages and frameworks
- Solid experience designing, building, and consuming RESTful APIs
- Proficiency with modern front-end frameworks such as React, Vue, or Angular
- Understanding of front-end performance best practices
- Strong SQL development skills
- Experience working with relational databases
- Experience with source control tools such as Git
- Experience with modern branching, PR, and code review workflows
- Experience or exposure to Agile development methodology
- Exposure to ML workflows, whether working alongside data scientists, integrating model APIs, or building ML-adjacent tooling
- Familiarity with LLM-based systems and ML frameworks
- Familiarity with the Model Context Protocol (MCP)
- Experience with cloud data warehousing and analytics engineering, particularly Snowflake and dbt
- Experience working in cloud environments such as AWS
- Experience with containerization tools such as Docker and Kubernetes
- Familiarity with CI/CD pipelines and DevOps practices
Benefits
- Trusted, empowered, and supported work environment
- Room to grow
- Tools to succeed
- Collaborative team support
- Outcomes valued over hours
- Curiosity valued over perfection
- Collaboration valued over ego
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