Intelliswift - An LTTS Company
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, 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
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Information Technology
IT Services and IT Consulting and Financial Services
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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, 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
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Information Technology
IT Services and IT Consulting and Financial Services
#J-18808-Ljbffr