Job Description
The AI Innovation and Solutions (AIS) team operates with the speed and spirit of a startup, focused on rapidly prototyping and building production‑grade, cloud‑native AI applications that integrate cutting‑edge AI capabilities to directly address the critical needs of our businesses.
Our primary goal is to demonstrate the transformative potential of AI within the firm through accelerated application delivery, rapidly deploying impactful solutions, and then seamlessly transferring the application code, cloud integration patterns, robust data models, and operational knowledge to respective business and engineering teams.
This hands‑on engineering role is pivotal in shaping the future of AI adoption at Goldman Sachs by building reliable, highly scalable, cloud‑optimized AI‑powered products and fostering a culture of innovation and rapid, continuous delivery.
Key Responsibilities
- Rapid prototyping and application development: lead end‑to‑end development of applications that integrate AI/ML models, from architectural design to deployment.
- Business partnership and solution architecture: collaborate with business and engineering teams to understand challenges, identify high‑impact opportunities, and translate requirements into robust, cloud‑optimized application architectures.
- Solution implementation and delivery: architect, implement, and deliver scalable, maintainable cloud‑native AI applications, ensuring integration with existing systems, applying software engineering, data modeling, DevOps/MLOps, and cloud security best practices.
- Knowledge transfer and enablement: provide documentation, training sessions, mentorship, and pair‑programming to empower teams to own and maintain AI‑powered applications.
- Technology and innovation leadership: stay abreast of the latest advancements in application development, AI/ML technologies, data management platforms, and operational best practices; evaluate and recommend new tools, techniques, and architectural patterns.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related quantitative field.
- 5+ years of hands‑on software engineering experience, with a proven track record of building and deploying robust applications and significant experience integrating AI/ML models.
- Experience building and deploying end‑to‑end applications that leverage LLMs, prompt engineering, API integration, and agentic frameworks.
- Strong proficiency in Python, Java, or Go, and experience integrating with AI/ML frameworks such as TensorFlow or PyTorch.
- Ability to translate complex business requirements into well‑defined, cloud‑optimized application architectures and scalable data models.
- Extensive experience with major cloud platforms (AWS, Azure, GCP), including serverless, containerization, and managed AI/ML services; strong command of DevOps/MLOps best practices.
- Excellent communication skills, able to articulate complex technical concepts to technical and non‑technical stakeholders.
- Strong collaboration and interpersonal skills, with a passion for mentoring and enabling others.
- Proven ability to lead or significantly contribute to cross‑functional projects.
Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
#J-18808-Ljbffr…