We are seeking a Staff Engineer for our AI Incubation team.
This role reports to the Chief Scientist and is a key member of a new team responsible for leveraging our extensive dataset of customer interactions to develop and validate new product capabilities.
The primary responsibility of this role is to rapidly prototype and test new Generative AI concepts, demonstrating a strong entrepreneurial spirit by transforming nascent ideas into tangible proofs-of-concept with speed and agility. Working closely with a Data Scientist, you will translate ideas from customers and internal stakeholders into functional proofs-of-concept to evaluate their technical feasibility and business potential. This role requires a self-starter who thrives on building from the ground up, embracing the challenge of bringing innovative AI solutions to life from initial concept.
Responsibilities:
Prototyping: Design, build, and deploy functional prototypes for new Generative AI features, utilizing production data sources to demonstrate technical feasibility.
Architectural Design: For validated prototypes, create high-level architectural designs and documentation to guide production implementation by core engineering teams. Ensure designs account for scalability, reliability, and security requirements.
Technology Evaluation: Evaluate emerging Generative AI technologies, including new models, frameworks, and architectural patterns (e.g. agentic frameworks, MCPs). Assess their applicability to our product and technical environment.
Collaboration: Collaborate with data scientists, product managers, and engineers throughout the prototyping lifecycle. Participate in technical discussions with customers and internal stakeholders to refine requirements.
Technical Guidance: Provide technical guidance to ensure that proposed AI features are aligned with engineering best practices, data constraints, and architectural standards.
This role reports to the Chief Scientist and is a key member of a new team responsible for leveraging our extensive dataset of customer interactions to develop and validate new product capabilities.
The primary responsibility of this role is to rapidly prototype and test new Generative AI concepts, demonstrating a strong entrepreneurial spirit by transforming nascent ideas into tangible proofs-of-concept with speed and agility. Working closely with a Data Scientist, you will translate ideas from customers and internal stakeholders into functional proofs-of-concept to evaluate their technical feasibility and business potential. This role requires a self-starter who thrives on building from the ground up, embracing the challenge of bringing innovative AI solutions to life from initial concept.
Responsibilities:
Prototyping: Design, build, and deploy functional prototypes for new Generative AI features, utilizing production data sources to demonstrate technical feasibility.
Architectural Design: For validated prototypes, create high-level architectural designs and documentation to guide production implementation by core engineering teams. Ensure designs account for scalability, reliability, and security requirements.
Technology Evaluation: Evaluate emerging Generative AI technologies, including new models, frameworks, and architectural patterns (e.g. agentic frameworks, MCPs). Assess their applicability to our product and technical environment.
Collaboration: Collaborate with data scientists, product managers, and engineers throughout the prototyping lifecycle. Participate in technical discussions with customers and internal stakeholders to refine requirements.
Technical Guidance: Provide technical guidance to ensure that proposed AI features are aligned with engineering best practices, data constraints, and architectural standards.
Requirements:
Significant hands-on experience in software engineering, with a track record of building data-intensive applications.
Strong practical knowledge of the Generative AI stack, including LLMs (APIs and open-source models), RAG patterns, and agentic frameworks (e.g., LangChain, LlamaIndex).
Experience with cloud-native architecture, particularly on AWS (e.g., Bedrock, S3, Lambda, SageMaker), and an understanding of microservices and data pipelines.
A product-oriented mindset with the ability to translate business needs into technical solutions.
Strong communication skills for effective collaboration with technical and non-technical stakeholders.
Advanced proficiency in Python or Java and common libraries for AI/ML development and backend services is a plus.
A Bachelors degree in Computer Science, Engineering, or a related field is preferred.
Significant hands-on experience in software engineering, with a track record of building data-intensive applications.
Strong practical knowledge of the Generative AI stack, including LLMs (APIs and open-source models), RAG patterns, and agentic frameworks (e.g., LangChain, LlamaIndex).
Experience with cloud-native architecture, particularly on AWS (e.g., Bedrock, S3, Lambda, SageMaker), and an understanding of microservices and data pipelines.
A product-oriented mindset with the ability to translate business needs into technical solutions.
Strong communication skills for effective collaboration with technical and non-technical stakeholders.
Advanced proficiency in Python or Java and common libraries for AI/ML development and backend services is a plus.
A Bachelors degree in Computer Science, Engineering, or a related field is preferred.
This position is open to all candidates.