AI Systems Engineer

The Generative AI, Conversational AI & Integration Engineer/Developer is responsible for delivering end-to-end application development, AI solution design, systems integration, cloud infrastructure management, operational support, and continuous improvement across a large-scale enterprise technology ecosystem. This role supports the full lifecycle of digital solutions, including projects, service requests, enhancements, maintenance, and ongoing operational support.

The ideal candidate combines expertise in Generative AI, Conversational AI, cloud technologies, API integrations, and enterprise application support while driving innovation, operational excellence, and strategic technology advancement. This position is responsible for developing, integrating, supporting, and evolving AI-driven and enterprise technology solutions that enable business growth and operational efficiency.

Roles and Responsibilities :

Generative AI, Conversational AI & Integration

• Design, develop, implement, and support Generative AI and Conversational AI solutions.
• Build and maintain intelligent virtual assistants (IVAs), chatbots, copilots, and AI-powered customer experiences.
• Develop conversational experiences using Google DialogflowCX, Google Conversational Agent and related technologies.
• Integrate Large Language Models (LLMs), AI orchestration frameworks, and enterprise AI services into business applications.
• Develop and maintain web services, APIs, and enterprise integrations.
• Support Media Gateway technologies and related integrations.

Cloud & Infrastructure Management

• Administer and support Google Cloud Platform (GCP) environments.
• Manage compute resources, servers, environments, and cloud-based services.
• Ensure system performance, scalability, reliability, and security.

Quality Assurance, Security & Operational Support

• Support remediation activities from security audits.
• Conduct quality assurance testing to ensure solution quality and compliance.
• Provide ongoing maintenance and operational support for enterprise applications and AI platforms.
• Support platform administration and application operations.
• Troubleshoot and resolve production issues while collaborating across technical teams.

Application Development & Lifecycle Management

• Support projects, service requests, enhancements, and operational initiatives.
• Deliver solutions throughout the full software development lifecycle, including requirements, design, development, testing, deployment, and support.
• Collaborate with business stakeholders, architects, and technical teams to deliver scalable solutions.
• Continuously improve platform stability, performance, and user experience.

Innovation & Continuous Improvement

• Research, evaluate, and prototype emerging AI technologies and integration patterns.
• Advance Generative AI and Conversational AI capabilities through innovation and experimentation.
• Recommend modern architecture, integration frameworks, and development best practices.
• Identify opportunities to improve operational efficiency, automation, scalability, and customer engagement.
• Contribute to long-term technology roadmaps and strategic initiatives.
• Participate in cross-training initiatives to expand team capabilities and reduce knowledge silos.
• Experience designing, developing, and supporting Generative AI and Conversational AI solutions.
• Experience with LLMs, prompt engineering, retrieval-augmented generation (RAG), AI orchestration frameworks, or related technologies.
• Experience with Google DialogflowCX and Conversational Agent or other conversational AI platforms.
• Experienced in using Docker and Kubernetes to containerize applications, orchestrate microservices, automate deployments, and maintain scalable, highly available cloud-based production environments.
• Strong knowledge of REST APIs, web services, and enterprise integration patterns.
• Experience with Google Cloud Platform (GCP) infrastructure and administration.
• Experience with Elasticsearch and Kibana for log aggregation, search optimization, monitoring, and troubleshooting distributed applications is a plus
• Knowledge of QA methodologies and complex testing practices.
• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to manage multiple priorities and competing workloads in a fast-paced environment.
• Excellent communication, collaboration, and stakeholder management skills.

**Key Competencies…