Software Engineer - AIOps

Job Responsibilities :

AIOps Engineer will implement the transformation of IT operations through the strategic application of Artificial Intelligence (AI), Machine Learning (ML) Big Data analytics and Robotic Process Automation (RPA). This critical role involves architecting and deploying cutting-edge automated solutions, including intelligent tools for actionable insights, leveraging technologies such as leading RPA platforms, advanced machine learning algorithms, and robust data analysis frameworks. AIOps Engineer will be a driving force for innovation, pioneering new approaches and technologies to enhance the performance and agility of backend, infrastructure, operational, and finance teams.

Essential Duties and Responsibilities

• Architect and implement AI/ML algorithms to boost IT operational efficiency and resilience.
• Develop scalable AI platforms for predictive analytics and proactive system optimization.
• Deploy machine learning models for automated incident resolution and operational intelligence.
• Build advanced data analytics system to extract actionable insights from big data.
• Create interactive dashboards for real-time monitoring of key operational metrics and trend analysis.
• Formulate data strategies to maximize value and drive continuous IT improvement.
• Identify and implement RPA solutions to automate repetitive tasks and streamline workflows.
• Collaborate with cross-functional teams to integrate AI, data analytics, and RPA for enhanced IT operations.
• Demonstrate strong interpersonal and communication skills to effectively engage both technical and non-technical stakeholders.
• Flexibly adapt to additional tasks and evolving priorities, ensuring alignment with organizational goals.

Requirements

• Bachelor's degree in Computer Science, IT, or a related field; 3+ years of relevant experience.
• Proficiency in at least two programming languages/frameworks (e.g., Python with Django, PHP with Laravel, or LangGraph for AI orchestration).
• Expertise in data preparation, model training, and big data analytics using tools such as Kafka, Anaconda, and Jupyter Lab.
• Strong experience with advanced AI/ML techniques, including LLM fine-tuning, reinforcement learning, and generative AI frameworks (e.g., Hugging Face Transformers, LangChain).
• Experience with vector databases and retrieval-augmented generation (RAG) techniques for AI-driven applications.
• Hands-on experience with RPA technologies (e.g., Automation Anywhere 360, RPA Bot frameworks) and AI/ML solution development.
• Solid experience with relational and NoSQL databases (e.g., MySQL, MariaDB, CouchDB, Redis) and SQL.
• Familiarity with version control (Git), Agile methodologies, and CI/CD pipelines.
• Experience with cloud platforms (e.g., AWS, Azure) and containerization technologies (Docker).
• Exposure to AIOps practices, including model deployment, monitoring, and automated retraining using tools like MLflow, Kubeflow, or Vertex AI.
• Strong analytical, problem-solving, and communication skills, with a proven ability to collaborate effectively in cross-functional teams.
• Ability to work independently, manage multiple projects, and adapt in a dynamic environment.