AI Software Engineer

Life at Hearst - Hearst (inactive)•Tampa, FL

11d

About The Position

The AI Software Engineer is a specialist in applying artificial intelligence and large language models (LLMs) to enhance and scale software engineering practices on the SaaS platform. This role bridges deep technical expertise with innovative automation, enabling the organization to solve complex engineering challenges and drive efficiency beyond traditional approaches. The AI Engineer collaborates across teams to design, implement, and maintain intelligent systems and tools that optimize workflows, reduce manual effort, and accelerate delivery.

Requirements

Minimum of 6 years of software engineering, with proven experience designing, implementing, and maintaining intelligent systems and tools that optimize workflows.
Advanced proficiency in AI/ML frameworks and LLM integration (e.g., Bedrock, OpenAI, GCP).
Strong programming skills in languages such as Python, Java, and experience with cloud platforms.
Demonstrated ability to design and deploy AI-powered automation tools for software engineering.
Excellent problem-solving, analytical, and communication skills.
Ability to work cross-functionally and influence engineering practices.
Commitment to continuous learning and adoption of emerging technologies.
Maintain a high level of professionalism, accountability, and responsiveness in all stakeholder and client interactions.

Responsibilities

Design and develop AI/LLM-powered solutions to automate software engineering tasks, such as test case identification, code review assistance, and defect prediction.
Build systems that automatically identify test cases requiring addition, modification, or deletion after implementation changes.
Create tooling and platforms that increase engineering scale and productivity without increasing headcount.
Integrate AI-driven analytics and recommendations into development pipelines to improve code quality and release velocity.
Collaborate with product managers, stakeholders, and engineering teams to identify opportunities for AI-driven automation and process improvement.
Mentor team members on AI/ML best practices and promote adoption of intelligent tooling.
Ensure robust testing, security, and reliability of AI-enabled solutions.
Stay current with advancements in AI, LLMs, and automation technologies, and evaluate their applicability to the SaaS platform.
Participate in scrum ceremonies and story refinement.
Deliver value to clients faster and at scale by leveraging AI-driven automation and intelligent systems.
Build and grow client trust organically as a product advisor by proving an ongoing value through accountability, proactive communication and transparency, while providing tailored solutions aligned to each client’s goals and use cases.