Senior AI Engineer Responsibilities Architect and implement scalable AI applications, including chatbots, search platforms, and autonomous agent workflows Collaborate directly with business stakeholders to understand their challenges and recommend smart, LLM-driven solutions Create data pipelines, design smart prompt strategies, and build testing frameworks to ensure our AI models are safe, accurate, and cost-effective Establish coding standards, perform code reviews, and mentor junior developers in AI best practices Run quick experiments, build prototypes to test new models, and stay current with emerging AI research and tools Requirements 3+ years of experience as a Senior Software Engineer delivering production-grade AI, Machine Learning, or LLM-based solutions Strong proficiency in Python (especially web frameworks like FastAPI) and a solid grasp of NLP concepts (semantic similarity, tokenization, text classification) Hands-on experience with modern AI patterns, particularly RAG (Retrieval-Augmented Generation) and AI Agents Familiarity with major LLM APIs (OpenAI, Anthropic, Bedrock) and framework tools (like LangGraph or LlamaIndex) Experience deploying AI applications at scale, managing cloud costs, and evaluating model quality (using retrieval metrics or LLM-based evaluation) Ability to quickly spin up user interfaces using Streamlit, Gradio, or similar tools Ability to explain complex technical ideas clearly to both developer teams and non-technical clients Strong English communication skills (B2 level or higher) Nice to have Development experience with TypeScript Experience incorporating AI into the SDLC (using tools like GitHub Copilot or Cursor to write, test, and review code) Cloud expertise with AWS or Azure (specifically Azure OpenAI or AWS Bedrock) Experience using Databricks (MLflow, Agent Bricks, etc.) for data or model workflows Knowledge of advanced search/retrieval systems (vector databases, semantic search, rerankers) Familiarity with emerging open-source protocols (like Model Context Protocol - MCP) or LLM monitoring tools (like LangSmith or Arize Phoenix)