Senior AI Engineer (Contract)

📋 Description

• • Build AI-powered integrations and data connectors to unify company data sources including Google Workspace, Slack, Jira, GitHub, Snowflake, and Confluence for AI systems
• • Design and maintain knowledge base pipelines, MCP integrations, and API connections that enable AI tooling across internal teams in Finance, Compliance, Product, and QA
• • Work within security and data governance frameworks to ensure all integrations are compliant, safe, and appropriately scoped for enterprise use
• • Support non-engineering teams in creating their own AI-powered workflows and internal tools using rapid app builder platforms, providing templates, guardrails, and reusable components
• • Develop and contribute to Lendable’s internal automation platform using tools such as AWS Bedrock, n8n, and custom-built solutions
• • Own end-to-end delivery of AI solutions—from identifying high-leverage use cases with the Product Manager and engineering lead, through design, development, deployment, and ongoing monitoring of impact
• • Measure and optimize outcomes by tracking metrics such as time saved, reduction in manual errors, and team adoption rates to ensure tools deliver tangible efficiency gains
• • Experiment with emerging AI techniques, LLM application patterns, embeddings, and AI tooling to identify and implement innovations that move the needle on internal productivity
• • Collaborate directly with end users across departments to understand pain points, validate assumptions, and iterate rapidly on prototypes based on real-world feedback
• • Ship functional tools quickly and iterate based on usage data, ensuring solutions are adopted within weeks of deployment
• • Maintain full ownership of deployed tools, including monitoring performance, troubleshooting issues, and evolving features based on changing team needs
• • Engage with the frontier of commercial AI tooling by evaluating and integrating new LLM providers, vector databases, and automation frameworks
• • Contribute to internal tooling with frontend development using Next.js or React to build intuitive interfaces for non-technical users
• • Balance speed and scalability by building solutions that are both immediately useful and sustainable at scale across a growing organization
• • Act as a bridge between technical teams and business stakeholders, translating operational friction into automated AI-driven solutions
• • Drive adoption by demonstrating clear value, providing training, and ensuring tools are intuitive and reliable enough for widespread use
• • Stay informed on evolving AI regulations and best practices to ensure all implementations remain ethical, compliant, and aligned with company policy
• • Partner with security and data teams to ensure AI systems do not introduce vulnerabilities or expose sensitive information
• • Document processes, integrations, and usage guidelines to empower teammates to independently use and extend AI tooling
• • Participate in continuous improvement cycles: ship, measure, learn, repeat, with a focus on incremental, measurable impact