AI Automation engineer

Are you passionate about leveraging AI to drive transformative changes within an organization? Do you enjoy working collaboratively with cross-functional teams to infuse AI capabilities into various business functions? Automation & AI Center of Excellence (CoE), stands at the forefront of innovation, leveraging the latest advancements in Automation & Generative AI to drive internal transformation. Join us in the pursuit of not just solving business challenges across Allianz Technologys Infrastructure, but reshaping the landscape for our employees through creative AI solutions. Immersing ourselves in the technology we deliver to our clients, we're not just adapting to change; we're driving it.

Job Summary:

We are seeking a dynamic and experienced Lead AIOps and Automation Engineer to drive the design, implementation, and optimization of cutting-edge automation and AIOps solutions . This role will involve leveraging AI, cloud technologies, and integration frameworks to enhance IT operations, scalability, and resilience. As a key member of our team, you will lead initiatives that modernize IT, streamline processes, and enable proactive decision-making through intelligent automation.The ideal candidate will have extensive experience in AIOps, Automation, Generative AI, Conversational AI, and IT Infrastructure & apps, with a strong focus on cloud technologies such as AWS and Azure. Additionally, experience with development in "Amelia AIOps software is required. The Lead Automation Engineer will be responsible for designing, implementing, and optimizing intelligent automation solutions to enhance our IT processes and operations and drive innovation.

Key Responsibilities:

• Lead the development and implementation of advanced automation strategies using AIOps Automation, Generative AI, and Conversational AI to enhance IT operations and efficiency.
• Lead the development of scalable advanced automation solutions for IT processes & operations, CI/CD pipelines, infrastructure as code, and cloud operations. Identify opportunities to eliminate manual processes and drive efficiency using automation, AI tools and frameworks (e.g., Amelia AIOps, Ansible, Terraform, etc.).
• Design and deploy scalable, reliable, and secure cloud AI & Automation solutions on AWS and Azure platforms, emphasizing Azure OpenAI and other Azure AI solutions.
• Develop and integrate automation solutions using Amelia AIOps platform to optimize IT and operational processes.
• Build and maintain integrations between IT systems, cloud platforms, and third-party services to enable seamless data exchange and workflows. Develop APIs and connectors for enabling automated orchestration across diverse platforms.
• Implement GitOps practices to streamline and automate deployment processes, ensuring consistency and reliability.
• Collaborate with cross-functional teams to identify automation opportunities and deliver innovative, impactful solutions.
• Mentor and guide junior engineers, fostering a culture of excellence in automation best practices and emerging technologies.
• Stay abreast of the latest trends and advancements in AI, cloud computing, and automation technologies to drive continuous innovation.
• Ensure compliance with security policies and best practices across all automation and cloud initiatives.
• Design and develop generative AI models for diverse applications using frameworks such as RAG ; Langchain etc
• Collaborate with cross-functional teams to optimize and enhance cloud automation processes, ensuring seamless integration.
• Research and implement new automation tools and techniques to continuously improve operational efficiency and innovation.
• Demonstrate familiarity with Cloud GenAI platforms, such as Azure Open AI , Bedrock Agents, to leverage their capabilities effectively.
• Experience in integrating multi-agent systems for data aggregation within agentic workflows to enhance data processing.
• Apply knowledge of MLOps pipelines for deploying and monitoring AI models, ensuring robust performance and reliability.

Qualifications:

• 7+ years of experience working in the AI & Automation field
• Proven experience in designing and implementing AIOps solutions in large-scale environments; strong expertise as an Automation Engineer with a focus on AIOps, Generative AI, and Conversational AI.
• Hands-on experience with Amelia AIOps software and integrations is a must
• Strong knowledge of AI/ML techniques applied to IT operations.
• Proficiency with automation tools (e.g., Ansible, Puppet, Terraform, Chef etc). Expertise in cloud platforms (AWS, Azure, GCP), with hands-on experience in automation and orchestration.
• Solid understanding of APIs, web services, and integration technologies (e.g., REST, GraphQL, Kafka). Proficiency in scripting/programming languages (Python, Java,Bash, etc.). Familiarity with observability tools (e.g., Splunk, Dynatrace, New Relic) and ITSM tools (e.g., ServiceNow)
• Strong background in machine learning and deep learning algorithms. - Proficiency in Python, TensorFlow, and PyTorch, Huggingface for developing AI models.
• Generative AI frameworks – Langchain, LlamaIndex,
• Agentic Frameworks - AutoGen, Semantic kernel, crewAI, promptflow,Langflow, Langraph
• Deep understanding of transformer architectures and diffusion models
• Experience in generative AI techniques such as GANs and VAEs. - Ability to design and implement scalable and efficient AI systems. Experience working with DevOps including but not limited to container technologies like Docker & Kubernetes, as well as Cloud Native technology stack such as Argo, Helm, etcd, and Envoy
• Strong communication, problem solving and leadership skills, with the ability to work collaboratively with diverse teams.
• Certifications in AWS, Azure, Generative AI or relevant AI technologies are a plus.

Technical Requirements:

• Extensive experience with infrastructure as code (IaC) tools such as Ansible, Terraform, or CloudFormation.
• Proficiency in CI/CD tools like Jenkins, GitLab CI/CD, or similar.
• Experience with containerization and orchestration tools such as Docker and Kubernetes.
• Knowledge of monitoring and logging tools such as Prometheus, Grafana, ELK Stack, or similar.
• Familiarity with RESTful APIs, SOAP UI, and microservices architecture for integration development.
• Understanding of network protocols, security, and cloud networking.
• Experience with version control systems such as Git, specifically GitHub Enterprise (GHE).
• Implementation and management of GitOps practices.
• Experience with Disaster Recovery (DR) planning and implementation.
• Knowledge of IT Service Management (ITSM) frameworks and tools.
• Expertise in designing and maintaining High Availability (HA) systems.
• Experience with AI model development and deployment, including machine learning and deep learning frameworks.
• Familiarity with natural language processing (NLP) and conversational AI tools.

  Role & responsibilities