Lead AI Engineer

We are looking for a Lead AI Engineer to drive the development, implementation, and evolution of advanced AI capabilities that support a broad spectrum of strategic business initiatives across our organization. This role provides a unique opportunity to lead high-impact AI projects by partnering deeply with cross-functional teams to create robust, scalable solutions.

Responsibilities

• Lead the design, development, and delivery of AI systems and components tailored to diverse product and organizational needs
• Define and prioritize product objectives into concrete technical strategies while contributing to team-wide plans
• Guide the creation, testing, and integration of AI solutions such as LLM-based systems, RAG pipelines, intelligent agents, and orchestration architectures
• Architect systems that extract structured insights, classify expansive datasets, and produce content aligned with enterprise-wide ontologies
• Drive the development of a shared AI platform emphasizing reusability, maintainability, and streamlined developer workflows
• Optimize AI systems to ensure peak performance, cost-efficiency, scalability, and operational stability
• Evaluate emerging trends in AI/ML and lead the selection and integration of new tools and technologies
• Facilitate collaboration with Product Managers and Engineering leaders, shaping requirements and technical approaches for complex initiatives
• Provide clear, proactive communication on technical tradeoffs, challenges, risks, and alternatives
• Take ownership of complex projects, ensuring timely delivery and guiding team members toward collective goals
• Establish technical standards and best practices that balance speed, quality, and scalability

Requirements

• 6+ years of professional software engineering experience
• 3+ years of experience designing, deploying, and scaling production AI/ML systems
• Advanced proficiency in Go (preferred) or similar modern backend languages like Python, PHP, Java, or Scala
• In-depth familiarity with GenAI ecosystems, such as OpenAI, Anthropic, Hugging Face, or LangChain
• Proven expertise in using LLMs for NLP tasks, including text analysis, structured extraction, summarization, and classification
• Extensive experience working with cloud environments (AWS, GCP, or Azure) and building MLOps workflows at scale
• Hands-on experience with vector databases, inference engines, and robust data storage solutions
• Strong SQL capabilities, with expertise in handling complex structured and semi-structured datasets
• English proficiency at a B2+ level

Nice to have

• Familiarity with frontend frameworks such as React or Angular
• Proven experience in designing internal systems leveraged across multiple teams and departments
• Deep understanding of large-scale taxonomies and ontologies for structured classification, tagging, or content generation
• Experience managing structured data outputs (e.g., JSON schemas, validation frameworks, or output parsing systems)