Senior Software Engineer

Introhive

4d•Remote

About The Position

Introhive is seeking a Senior Software Engineer to join our AI/ML team and help shape the next generation of our enterprise intelligence platform. You'll work at the intersection of cutting-edge AI capabilities and world-class software delivery, building the interfaces, APIs, and tooling that bring our AI-powered features to life. If you thrive in a collaborative, fast-moving environment and love solving complex technical problems, we'd love to meet you.

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; we also use Python)
Ability and desire to learn new languages and frameworks
Solid experience designing, building, and consuming RESTful APIs
Proficiency with modern front-end frameworks (e.g. React, Vue, or Angular) and an understanding of front-end performance best practices
Strong SQL development skills and experience working with relational databases
Experience with source control tools like Git and modern branching, PR, and code review workflows
Experience or exposure to Agile development methodology

Nice To Haves

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 (AWS) and with containerization tools (Docker, Kubernetes)
Familiarity with CI/CD pipelines and DevOps practices

Responsibilities

Extend our 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 complex model outputs and user requirements into elegant, 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 that enables teams to more effectively deploy, test, monitor, and operate 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, helping translate business goals into sound architectural decisions
Work independently and collaboratively within the team