The Internal AI Solutions Team leads the transformation of the company’s internal processes through Generative AI, enhancing how we work across the organization. By equipping teams like Finance, Commercial, and Talent with AI-powered tools and techniques, this team empowers departments to expand their reach and impact, thus ultimately driving the success of the company.
We’re a small team with a style reminiscent of an early-stage company, characterized by highly generalist roles and a proactive attitude. We work very closely with key stakeholders in each vertical at Sword to learn their processes and understand how we can help them succeed through AI.
What you’ll be doing:
Implementing and optimizing AI-driven solutions to improve internal operations and workflows, under the strategic guidance of the Head of Internal AI Solutions;
Translating strategic objectives into functional software applications using specific technologies;
Handling both front-end and back-end development tasks, ensuring seamless integration and performance across our tech stack;
Proactively identifying and resolving technical challenges to enhance system functionality and user experience.
What you need to have:
At least 3 years of experience as a Senior Software Engineer, with strong hands-on proficiency in JavaScript (React, Node.js) and Python;
Proficiency in SQL;
Hands-on experience with LLM APIs (OpenAI, Anthropic, etc.) or open-source models;
Familiarity with cloud services (AWS, Azure, Google Cloud), particularly for deploying and managing AI-powered applications;
Experience integrating AI capabilities into internal tools (e.g., Slack bots, internal dashboards, or workflow assistants);
Strong analytical and problem-solving skills, with a track record of handling complex projects that require integrating multiple systems;
A proactive approach to process improvement, demonstrating a track record of enhancing system efficiencies and effectiveness;
Strong communication skills for effective collaboration across multidisciplinary teams.
What we would love to see:
Familiarity with Retrieval-Augmented Generation (RAG) pipelines and integrating structured/unstructured data into LLM workflows;
Practical experience building or orchestrating AI agents;