AI Engineering Lead

This is a fully remote position, open to applicants in Ukraine, +2 more states.

📋 Description

• Oversee the technical design and architecture of AI agent platforms and multi-agent workflows utilizing LangChain and LangGraph.

• Actively engage in the development of AI agents.

• Incorporate LLMs from various providers, including OpenAI, Anthropic, and Azure OpenAI, into production-quality agent pipelines.

• Develop and enhance CI/CD, containerization, and infrastructure-as-code methodologies for the team.

• Establish and uphold AI observability across agent systems, including tracing execution paths, monitoring performance, tracking costs, and identifying anomalies.

• Mentor and support engineers through code reviews, architectural discussions, and knowledge sharing sessions.

• Collaborate with product managers, solution architects, and stakeholders to ensure technical implementation aligns with business goals.

• Maintain system reliability, scalability, and maintainability through clean architecture, automated testing, and best practices in deployment.

• Help define engineering standards, development workflows, and documentation practices within the team.

• Contribute to technical solutions for AI-focused proposals during pre-sale processes.

⛳️ Requirements

• Over 5 years of experience in software engineering with a strong emphasis on AI/ML systems.

• Proficient Python skills, including async programming and design patterns.

• Proven experience in creating AI agents and multi-agent systems with LangChain and LangGraph.

• Strong practical expertise in LLM integration patterns such as prompt engineering, function/tool calling, retrieval-augmented generation (RAG), embeddings, and vector search.

• Extensive experience with cloud platforms like AWS and/or Azure, covering deployment, scaling, and management of AI workloads.

• Solid foundational knowledge of ML, including model training, evaluation, inference pipelines, and the complete ML development lifecycle.

• Strong expertise in CI/CD pipelines.

• Practical experience with containerization and orchestration in production settings.

• Hands-on knowledge of infrastructure-as-code tools for reliable and repeatable management of cloud resources.

• Experience in implementing AI observability.

• Competence in utilizing AI tools for routine tasks (e.g., Claude Code, Cursor, Advanced prompting, etc.).

• Experience in designing and building robust APIs (FastAPI, Flask, or similar) and integrating them into larger system architectures.

• Proficient in SQL and NoSQL databases.

• Capability to lead technical discussions, conduct insightful code reviews, and mentor team members.

• Upper-Intermediate English proficiency or higher.

• Strong knowledge of core ML frameworks.

• Hands-on experience with AWS SageMaker and the broader AWS ML ecosystem.

• Solid comprehension of the entire ML lifecycle.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Opportunities for professional development and continuous learning.

• Flexible work hours and remote work options.

• Collaborative and inclusive team environment.

• Health and wellness programs.