Lead AI Engineer

We're seeking a talented, innovation-focused Lead Data Engineer to join our team and drive the creation of state-of-the-art Generative AI solutions. This role is perfect for someone who is enthusiastic about artificial intelligence and skilled at building systems that produce measurable business results. You'll collaborate with a dynamic team to build and launch AI-powered technologies that solve real-world problems, all within a supportive, collaborative, and future-oriented workplace. In this senior position, your role will extend beyond coding; you'll design intelligent systems, engage directly with clients as a consultant, guide and develop emerging talent, and transform cutting-edge AI research into real-world production systems. If Python, Natural Language Processing (NLP), and staying at the forefront of Generative AI excite you, we'd love to connect with you! Responsibilities Design and build scalable AI applications, including chatbots, search platforms, and autonomous agent workflows Work closely with business stakeholders to identify their pain points and propose effective, LLM-powered solutions Build data pipelines, develop intelligent prompt strategies, and construct testing frameworks that keep AI models accurate, safe, and cost-efficient Set coding standards, conduct code reviews, and guide junior developers on AI best practices Conduct rapid experiments, develop prototypes to evaluate new models, and keep up with the latest AI research and tools Requirements 5+ years as a Senior Software Engineer building production-grade AI, Machine Learning, or LLM-based solutions 1+ years in a leadership capacity Strong Python skills, particularly with web frameworks like FastAPI, plus knowledge of NLP concepts like semantic similarity, tokenization, and text classification Practical experience with modern AI approaches, especially RAG (Retrieval-Augmented Generation) and AI Agents Knowledge of leading LLM APIs (OpenAI, Anthropic, Bedrock) and tools like LangGraph or LlamaIndex Track record deploying AI applications at scale, controlling cloud expenses, and assessing model performance through retrieval metrics or LLM-based evaluation Ability to rapidly build user interfaces using tools such as Streamlit or Gradio Skill in communicating complex technical concepts clearly to both technical teams and non-technical clients Solid English communication abilities (B2 level or above) Nice to have Background in TypeScript development Hands-on experience integrating AI into the SDLC using tools like GitHub Copilot or Cursor for writing, testing, and reviewing code Proficiency with AWS or Azure, particularly Azure OpenAI or AWS Bedrock Experience with Databricks tools (MLflow, Agent Bricks, etc.) for managing data or model workflows Understanding of advanced search and retrieval technologies (vector databases, semantic search, rerankers), along with familiarity with new open-source protocols such as Model Context Protocol (MCP) or LLM monitoring platforms like LangSmith or Arize Phoenix