Lead AI Engineer

Responsibilities

• Drive technical vision and architecture by leading the design and implementation of highly scalable, robust enterprise AI applications, including complex multi-agent workflows, custom search engines, and end-to-end AI systems
• Partner closely with clients and business stakeholders to translate business goals into technical roadmaps and recommend high-impact, feasible LLM-driven solutions
• Establish engineering standards by setting the benchmark for code quality, architectural patterns, robust data pipelines, smart prompt management, and automated evaluation frameworks
• Foster a culture of learning and high performance through design reviews, development best practices, and active mentorship of junior and senior developers
• Direct R&D and innovation by guiding research on emerging models, framing prototyping strategies (PoCs), and standardizing the tools and frameworks used to stay on the bleeding edge of Generative AI

Languages

Required

• 5+ years of experience in a Lead, Principal, or Senior AI/Software Engineering role, with a track record of architecting and shipping complex, production-grade AI or ML-based solutions
• Master-level proficiency in Python (specifically FastAPI or equivalent web frameworks) and a strong foundation in core NLP concepts (semantic similarity, tokenization, NER, text classification)
• Expertise in modern Generative AI design patterns, particularly RAG (Retrieval-Augmented Generation), autonomous multi-agent networks, and tool integration
• Background in optimizing AI applications for performance, security (prompt injection mitigation, data privacy), cloud costs, and system evaluation using programmatic or LLM-as-a-judge approaches
• Capability to quickly direct and build intuitive UI/UX prototypes using Streamlit, Gradio, or equivalent

Nice to have

• At least 1 year of relevant leadership experience
• Outstanding leadership and communication skills to lead engineering discussions, bridge the gap between technical and non-technical audiences, and present technical architectures to executives and clients
• Strong English communication skills (B2 level or higher)
• Full-stack capabilities with TypeScript
• Experience incorporating AI into the SDLC to boost team efficiency using tools like GitHub Copilot, Cursor, or specialized agents for automation
• Cloud architecture expertise in AWS or Azure (specifically Azure OpenAI, AWS Bedrock, or cloud-native containerized deployments)
• Familiarity with Databricks (MLflow, Agent Bricks, Unity Catalog) for orchestrating data pipelines and model lifecycles

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