Cloud Developer

Position Summary:

As a Cloud Developer with a focus on Generative AI you will design and build an innovative application that transforms how developers interact with cloud technologies. Your work will help shape our agent-oriented software engineering (AOSE) journey. You will combine conversational AI intelligent workflows and integrated agents to automate and enhance developer experience using cloud at Fiserv.

Primary Responsibilities:

Leading the design development and implementation of an agentic customer engagement platform leveraging the latest Generative AI capabilities

Collaborating with other development teams to integrate agents tools and cloud services ensuring seamless functionality and efficient workflows

Monitoring operating and optimizing the solution for performance customer satisfaction and cost efficiency ensuring high availability and responsiveness.

Develop and integrate autonomous agents that can plan execute and monitor tasks across cloud platforms including retrieval-augmented generation tool use and workflow automation

Participating in code reviews technical discussions and contributing to the overall architectural strategy of AI solutions

Integrate large language models (LLMs) vector search and other ML capabilities to power conversational experiences and intelligent recommendations

Collaborate with software engineering and security teams to ensure new services and features are production-ready and meet reliability standards

Qualifications:

Familiarity with Agent Development Kit (ADK) Model Context Protocol (MCP) and strong skills in prompt engineering for optimizing Generative AI model outputs.

5 years of experience in software development with proficiency in at least one programming language (e.g. Python Go Java C)

Experience administrating cloud platforms (AWS GCP Azure) including networking security containerization storage data management and serverless technologies

Deep understanding of observability (monitoring alerting and logging) tools in cloud environments. Ability to set up and maintain monitoring dashboards alerts and logs

Familiarity with Continuous Integration/Continuous Deployment (CI/CD) tools for automated testing deployments provisioning and observability

Ability to manage and respond to incidents perform root cause analysis and implement post-mortem reviews

Understanding and practical experience with MLOps principles for managing the machine learning lifecycle

Experience with data management and engineering principles in a cloud context

Additional Qualifications a Plus:

Experience working with enterprise-scale financial services or other regulated industries

5 years of experience in SRE DevOps MLOps infrastructure or cloud engineering roles preferably supporting large-scale distributed systems.

Experience leading technical projects or mentoring junior engineers

Cloud Certifications: Certified Engineer Developer Architect DevOps