Engineer 

Job Description

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.

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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