Anblicks
Senior AI Engineer
Role Overview
  • Lead the design, development, and deployment of advanced AI systems
  • Build cutting-edge solutions across machine learning, NLP, generative AI, LLMs, and multi-agent orchestration
  • Drive innovation across our product portfolio by solving real-world problems
Key Responsibilities
  • Architect, build, and deploy production-grade AI/ML systems at scale
  • Design and develop RAG pipelines, agentic AI systems, and multi-agent orchestration solutions
  • Build intelligent automation flows and conversational AI agents using frameworks like LangGraph, LangChain, and Microsoft Copilot Studio
  • Develop time-series forecasting and anomaly detection models for real-world business use cases
  • Apply advanced prompt engineering and integrate Model Context Protocol (MCP) to connect AI agents with enterprise systems
  • Own the full AI project lifecycle — from data ingestion and preprocessing through model training, evaluation, deployment, and monitoring
  • Collaborate with data scientists, software engineers, and product managers to translate business needs into AI-powered solutions
  • Optimize model performance and ensure robustness, fairness, and explainability
  • Stay current with the latest AI/ML research and bring relevant advancements into our stack
Our Technology Landscape
  • Retrieval-Augmented Generation (RAG) pipelines
  • Agentic AI frameworks (e.g., LangGraph, LangChain)
  • Multi-agent orchestration systems
  • Model Context Protocol (MCP) integrations
  • Advanced prompt engineering
  • Time-series modeling, forecasting, and anomaly detection
  • Intelligent automation flows and workflow orchestration
  • Microsoft Copilot Studio for building and deploying custom copilots and conversational AI agents
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field (PhD preferred)
  • 5+ years of AI/ML engineering experience with a proven track record of shipping models to production
  • Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
  • Experience with cloud platforms (AWS, Azure) and MLOps tools
  • Strong understanding of data structures, algorithms, and software engineering principles
  • Solid grounding in software engineering best practices and system design
  • Experience designing and building automation workflows or process automation systems
  • Excellent problem-solving and communication skills

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