What are the responsibilities and job description for the Cloud Developer position at Intelliswift - An LTTS Company?
Job Posting Title: Cloud Developer
Location: Alpharetta, GA or Berkeley Heights, NJ
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