Staff Applied AI Engineer

Forward Financing•Boston, MA

19h•Remote

About The Position

The Staff Software Engineer - Applied AI will architect and develop systems, tools, and agents that use existing foundational AI models to deliver impactful AI-powered solutions. This expert generalist will integrate AI capabilities across diverse technology stacks and platforms in a fast-paced innovation lab environment, driving test-and-learn experiments with a focus on system design, scalability, and seamless AI service integration. The role translates business needs into technical implementations and contributes to an innovation team that experiments with and develops proof-of-concept solutions to address significant business opportunities. The engineer will collaborate with product managers, data scientists, and frontend engineers and document system designs, APIs, workflows, and integration patterns for knowledge sharing and operational continuity.

Requirements

Bachelor’s or master’s degree in Computer Science, Engineering, or a related technical discipline.
Demonstrated experience as a backend software engineer with strong programming skills; Python is preferred.
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 foundational model providers, AI APIs, data pipelines, and orchestration frameworks.
Practical expertise integrating third-party AI services and managing complex dependencies in multi-stack environments.
Strong problem-solving skills and a test-and-learn mindset, with the ability to prototype rapidly and develop iteratively.
Excellent communication skills to present technical concepts clearly to technical and business stakeholders.

Nice To Haves

Experience with Ruby or Go.
Familiarity with AI tools and frameworks such as 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 building APIs and backend components for real-time or near-real-time AI applications.

Responsibilities

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.
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, and data systems such as Snowflake.
Build experimentation frameworks that support iterative deployment of AI-driven functionality and rapid test-and-learn cycles.
Collaborate with product managers, data scientists, and frontend engineers to translate business needs into technical implementations.
Track developments in the AI ecosystem, frameworks, and tools to guide implementation decisions and technical evaluations of new AI capabilities.
Document backend system designs, APIs, workflows, and integration patterns for team knowledge sharing and operational continuity.