Senior AI Engineer (Portugal-based Remote/Hybrid)

At Sword, we’re building AI to heal billions and unlock humanity’s full potential. In doing so, we’re pioneering AI Care, a fundamentally new approach to healthcare built for medical reasoning, safety, and real-time treatment, not generic technology applied after the fact.

As both a clinical-centric frontier AI lab and an applied AI platform, Sword is reimagining how care is delivered at scale, removing traditional barriers like appointments, waiting rooms, and stigma so more people can access the care they need - and ultimately get back to lives lived in full.

Since 2020, Sword has expanded across Musculoskeletal, Women’s Health, Cardiometabolic, and Mental Health, and is now moving beyond the session to a fully AI-native, 24/7 care program that brings physical activity, therapeutic exercise, psychotherapy, nutrition, and behavior change into one connected experience.

More than 1 million members across three continents have completed over 15 million AI sessions, helping 2,000+ enterprise clients avoid more than $1 billion in unnecessary healthcare costs.

Backed by 59 clinical studies, 43 patents, and more than $500 million raised from leading investors including Khosla Ventures, General Catalyst, and Founders Fund, Sword is defining a new standard for healthcare.

The Internal AI Solutions Team

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.

AI Proficiency at Sword Health

AI fluency is a core expectation at Sword Health. Every candidate is assessed against our three-level framework — be ready to share real examples of how AI is already part of how you work.

Explorer (Level 1) — Uses AI daily to boost personal productivity

Builder (Level 2) — Creates workflows and tools that elevate the whole team

Integrator (Level 3) — Embeds AI into products and processes at scale

Every hire must demonstrate at least Level 1. The expected level will vary depending on the seniority of the role.

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;

Understanding of AI governance principles.