Lead AI SME

Description

We are seeking a highly skilled and experienced Lead AI Subject Matter Expert (SME) to join our team. As a Lead AI SME you will play a critical role in driving the development and implementation of artificial intelligence solutions within our organization. Your expertise in AI technologies and industry best practices will help guide our team in leveraging the power of AI to improve our products and services.

Responsibilities

• Lead the design development and deployment of AI models and algorithms.
  
• Provide technical guidance and mentorship to the AI team ensuring they have the necessary tools and knowledge to excel in their roles.
  
• Collaborate with crossfunctional teams to identify and prioritize AI opportunities that align with our business objectives.
  
• Conduct research and stay uptodate with the latest advancements in AI technologies frameworks and methodologies.
  
• Evaluate and select appropriate AI tools and platforms for different use cases.
  
• Design and implement data collection strategies to ensure the availability of highquality data for AI model training.
  
• Develop performance evaluation methodologies to measure the effectiveness and accuracy of AI models.
  
• Stay informed about industry regulations and ethical considerations related to AI and ensure compliance in all AI initiatives.
  

Requirements

• Bachelors degree in Computer Science Data Science or a related field. Masters degree preferred.
  
• Proven experience in developing and deploying AI models in realworld applications.
  
• Strong knowledge of machine learning algorithms deep learning frameworks and natural language processing techniques.
  
• Proficiency in programming languages commonly used in AI development such as Python.
  
• Excellent problemsolving skills with the ability to think creatively and critically.
  
• Strong communication and collaboration skills ability to convey complex AI concepts to nontechnical stakeholders effectively.
  
• Solid understanding of data management data cleaning and data preprocessing techniques.
  
• Familiarity with cloud platforms such as AWS or Azure and experience with big data frameworks like Apache Spark.
  

Understanding of event-driven architectures Distributed systems - How clusters are formed, Quorum management, Failure handling. 3 to 5 years of hands-on Experience in MQ or NATS broker or similar messaging solutions. Understanding of Kafka clustering would be good to have. Knows Client-Server communication aspects - sockets, TLS protocol etc Understands the concept of region and AZs. Provide L2 support production systems like application, database, middleware components, infrastructure and network components. Manage production incidents end-to-end within defined SLAs with focus on resolution rather than who caused it. Interact with various stakeholders such as Release managers, program leads, service managers, development and test leads Review operational readiness requirements such as monitoring and alerting, log rotation and resilience of the components and report the gaps Provide pre-implementation support with activities such as release notes review and implementation dry runs. Protect production components by running health checks monitoring latency and memory utilization. Automate day-to-day activities and propose changes that improve reliability Participate in CAB and provide feedback on change requests Support the DevOps team in testing the promoted pipelines and suggest automation of configuration items. Practice incident management best practices and perform RCA. Participate in disaster recovery tests and operational acceptance tests Analyze the technology stack that makes up the product and optimize recovery time objective. Work with team members spread across and time zones Share knowledge, document improvements and mentor junior resources It is good to have skills using Jenkins to orchestrate builds and link to Sonar, Maven, etc. to build out the CI/CD pipeline. Support deployments of code into multiple lower environments. Supporting current processes needed with an emphasis on automating everything as soon as possible. It is good to have skill to design, Implement, and enhance our deployment automation based on Chef. We need proven experience designing and implementing an overall release and deployment process. It is good to have skill to design and implement a Git based code management strategy that will support multiple environment deployments in parallel. Experience with automation for Branch management, code promotions, and version management. Engage in and improve the whole lifecycle of services from inception and design through deployment, operation, and refinement. Requirements MQ/EB Understanding of event-driven architectures Distributed systems - How clusters are formed, Quorum management, Failure handling. 3 to 5 years of hands-on Experience in MQ or NATS broker or similar messaging solutions. An understanding of Kafka clustering would be good to have. Knows Client-Server communication aspects - sockets, TLS protocol etc Understand the concept of region and AZs. Deployments MTF/Prod, Maintenance items (including stop/start, Disaster Recovery-related activities, etc.), CR for changes in MTF/Prod Good knowledge on Nginx Tools - Log Monitoring Tool - Splunk Application Monitoring tool - Dynatrace Ticketing incident/problem management tool - Remedy Dev-ops Basics - CI-CD Basics, Overview of Git, Bit-bucket, SonarQube, Ansible/Chef Skills - Linux & Shell Scripting ITIL / ITSM PL/SQL Troubleshooting Jenkins - CI/CD Groovy Scripting/Yaml Ansible/Chef Nginx Java / JEE Event-Driven Architectures MQ or NATS broker or similar messaging solutions. Kafka Client-server communication aspects - sockets, TLS protocol Understand the concept of region and AZs.