Role Overview
The Applied AI Engineer will architect and develop systems, tools and agents that leverage existing foundational AI models and deliver impactful AI-powered solutions. This role requires an expert generalist with deep technical skills who can integrate AI capabilities across diverse technology stacks and platforms. The engineer will work in a fast-paced innovation lab environment driving test-and-learn experiments, focusing on system design, scalability, and seamless AI service integration. You will be empowered to drive change by translating business needs into technical implementations that unlock business potential. You will be part of an innovation team that will be tasked with experimentation and developing proof of concept solutions to solve some of the company’s most exciting problems and to capture significant business opportunities.
In this role you will:
- Translate high-level business problems into functional AI solutions by creating and executing end-to-end solutions.
- Design, build, and maintain backend services and APIs that deploy and integrate AI-powered features using existing foundational models (e.g., OpenAI, Claude, Hugging Face, etc.).
- Implement scalable, reliable, and maintainable backend architecture supporting AI workflows, automation, and data processing pipelines.
- Integrate AI services into complex technology stacks, ensuring interoperability with microservices, AWS platform, and data systems (Snowflake).
- Enable rapid test-and-learn cycles by building experimentation frameworks that support iterative deployment of AI-driven functionalities.
- Collaborate closely with cross-functional teams including product managers, data scientists, and frontend engineers to translate business needs into technical implementations.
- Stay abreast of the AI ecosystem, frameworks, and tools to guide implementation decisions and technical evaluations for adopting new AI capabilities.
- Document backend system designs, APIs, workflows, and integration patterns clearly for team knowledge sharing and operational continuity.
Required Skills and Experience
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical discipline.
- Demonstrated experience as a backend software engineer with strong programming skills (Python preferred; experience with Ruby or Go is a plus).
- Proven ability to design and develop scalable backend systems, APIs, and distributed services.
- Strong understanding of cloud infrastructure and platforms, container orchestration, and deployment pipelines.
- Strong knowledge of AI ecosystem components including major foundational model providers, AI APIs, data pipelines, and orchestration frameworks.
- Practical expertise in integrating third-party AI services and managing complex dependencies in multi-stack environments.
- Effective problem solver with a test-and-learn mindset, capable of rapid prototyping and iterative development.
- Excellent communication skills to present technical concepts clearly to both technical and business stakeholders.
Preferred Skills
- Familiarity with AI tools and frameworks like AWS Bedrock, Langchain, vector databases, or similar AI orchestration technologies.
- Experience with automation, knowledge systems, and backend optimization related to AI-driven processes.
- Understanding of responsible AI principles, data privacy, and system reliability considerations.
- Experience in building APIs and backend components for real-time or near-real-time AI applications.