AI Engineer

Phantom is on a mission to connect the world to the freedom of open markets. Tens of millions of people all over the world use Phantom to access global markets that never close, including perpetuals, prediction markets, tokenized assets, stablecoins and memes. Phantom users are able to discover the markets that matter and the cultural moments that shape them, building conviction through real-time data and the verified performance of top traders. With self-custody and access to open networks at its core, Phantom lets them control their financial moves in the same app they use to safely store or spend money worldwide.

Phantom has reached #1 in Google Play’s finance category and consistently ranks in the top 50 apps across all categories. Check out our Forbes Fintech 50 and CNBC and Statista’s World’s Top Fintech Companies 2026!

We are around 180 people, fully remote, backed by a $150M Series C investment from a16z, Sequoia Capital and Paradigm.

About The Role At Phantom, we’re looking for an AI Engineer to help shape how AI is adopted and scaled across the company. You’ll play a key role in building the internal AI tools, integrations, and automation that enable teams to work smarter, move faster, and operate more efficiently.

This is a hands on engineering role focused on turning emerging AI capabilities into practical, reliable solutions that drive meaningful business impact. You’ll partner closely with teams across the organization to identify opportunities, build AI powered workflows, and establish the technical foundations that make AI accessible, secure, and scalable.

We’re looking for someone who enjoys building, experimenting, and shipping, with a strong understanding of modern LLM technologies and the engineering fundamentals required to bring AI solutions into production.

Responsibilities

• Build AI Solutions: Design, develop, and deploy AI powered tools, agents, and automation that streamline workflows and solve real business problems across the organization.
• Develop AI Integrations: Connect LLMs and AI applications with internal systems, APIs, and enterprise tools to enable seamless, intelligent workflows.
• Own AI Infrastructure: Build and maintain the underlying infrastructure, services, and integrations that support reliable AI applications across teams.
• Enable AI Adoption: Partner with stakeholders to identify opportunities for AI, translate business needs into technical solutions, and empower teams to leverage AI tools effectively.
• Build for Scale: Develop reusable components, frameworks, and tooling that make it easier for teams to build, customize, and maintain their own AI workflows.
• Ensure Security & Reliability: Implement appropriate access controls, monitoring, observability, and operational safeguards to ensure AI solutions are secure, reliable, and maintainable.
• Optimize AI Usage: Monitor model performance, usage, and costs while identifying opportunities to improve efficiency, quality, and business outcomes.
• Drive Innovation: Stay current with emerging AI technologies, evaluate new models and frameworks, and identify practical opportunities to bring new capabilities into the organization.

Qualifications

• Strong software engineering background with experience building and maintaining production applications, services, or internal platforms.
• Hands on experience developing applications using LLMs such as OpenAI, Anthropic Claude, or open source models.
• Proficiency in Python, TypeScript, or similar programming languages, with experience integrating APIs and building backend services.
• Experience building AI agents, workflow automation, or applications that leverage LLM orchestration frameworks.
• Familiarity with retrieval augmented generation (RAG), tool calling, structured outputs, prompt engineering, and modern AI application patterns.
• Experience integrating applications with enterprise tools, internal systems, and third party APIs.
• Understanding of cloud infrastructure, deployment practices, monitoring, and production reliability.
• Strong product mindset with the ability to translate ambiguous business problems into practical technical solutions.
• Ability to work independently, take ownership of projects, and collaborate effectively with both technical and nontechnical stakeholders.
• A genuine interest in AI and a bias toward experimentation, execution, and measurable impact.

Nice to Have

• Experience building…