Please mention DailyRemote when applying
Novisto is on a journey to become an AI-first organization. We believe artificial intelligence will reshape the workplace by automating repetitive tasks and enabling teams to focus on higher-value, strategic work.
The AI Builder will report to the Director, IT, Security & AI Enablement with a dotted line to the Principal Developer, Analytics & GenAI on the engineering side. The role will work closely with business teams across sales, marketing, product and customer success to identify high-value opportunities and build practical AI-enabled solutions. The role combines technical development and cross-functional collaboration to rapidly prototype, deploy and scale solutions that improve how work is done across the company.
This is fundamentally a full-stack engineering role. The majority of the work involves building the data pipelines, system integrations, and foundational infrastructure that make AI solutions possible, not just the AI layer itself. Strong engineering fundamentals matter as much as AI fluency here.
Key Responsibilities:
- Partner with departments to understand operational problems, scope technical solutions, and rapidly prototype and iterate based on real-world feedback.
- Design and build integrations between internal platforms and third-party APIs (HubSpot, Gong, Jira, Confluence, GitHub…), including authentication, error handling, and ongoing maintenance; build data pipelines that move, transform, and prepare data from internal systems for use in AI.
- Build and maintain MCP servers that connect enterprise tools to the internal AI platform.
- Build and deploy production-ready AI applications, including RAG pipelines, agentic workflows, and LLM integrations, with a pragmatic eye toward what actually works at scale.
- Contribute to foundational infrastructure decisions, data storage, service architecture, deployment patterns as the company's internal AI platform matures on Google Vertex AI.
- Ensure solutions meet production standards for security, access controls, responsible AI usage, and ongoing maintainability.
Job Requirements
- Bachelor's degree in Computer Science, Engineering or a related field, or equivalent practical experience.
- 2–5 years of experience in software engineering roles, with demonstrated ownership of production systems end-to-end.
- Solid full-stack engineering fundamentals — backend services, relational and document databases, REST and webhook integrations, async patterns, and cloud deployment (GCP preferred).
- Hands-on experience building and maintaining data pipelines and system integrations in production environments, not just application-layer prototypes.
- Practical experience with LLM-based systems in production — including RAG pipelines, agentic workflows, and LLM integrations — and sound judgment on when AI adds value over conventional approaches.
- Experience with agentic frameworks and tool-integration protocols — such as LangChain, LangGraph, Google ADK, or MCP (Model Context Protocol) servers.
- Curious, self-directed, and biased toward action — able to work directly with non-technical stakeholders, move fast in ambiguous situations, and drive problems to resolution without heavy oversight.
Preferred:
- Experience in ESG, sustainability or SaaS environments.
- Familiarity with Google Cloud Platform (Vertex AI, Cloud Run).
- Experience with MCP protocol or similar tool-integration patterns.
What we offer
Stop the endless job search. Our AI finds and applies to the best jobs for you.
Discover remote opportunities in Software Development
Answer easy questions
200,000+ jobs across 15+ categories
Get your best job matches
Only hand-screened, legit jobs
Find a remote job faster
No ads, scams, or junk
“ I was the first applicant for a remote marketing position that got listed on the company website the same day I applied. Had an interview within 48 hours!