EX Squared is hiring a Senior AI Engineer - Remote

We are seeking an exceptional Senior AI Engineer to spearhead the design, development, and implementation of scalable AI systems within an innovative integration and automation platform. This role encompasses working with advanced language models, retrieval-augmented generation frameworks, cloud AI services, and sophisticated data pipelines to construct robust, distributed, and high-performance AI applications. You will engage with interdisciplinary teams spanning engineering, product, and operations to transform intricate business requirements into dependable AI-driven solutions. The position presents an opportunity to pioneer cutting-edge technologies, provide mentorship to emerging engineers, and contribute to a globally distributed, remote-first environment dedicated to automation and cloud-scale solutions. Ideal candidates are hands-on, technically adaptable, and passionate about revolutionizing AI within enterprise systems. Accountabilities - Design, develop, and maintain large-scale, distributed AI systems and applications. - Implement and optimize AI capabilities, including LLM-based solutions, RAG pipelines, and NLP tools. - Collaborate with cross-functional teams to translate business requirements into technical solutions. - Mentor and support junior engineers, promoting best practices in AI development and cloud architecture. - Participate in architecture design, code reviews, and solution validation to ensure robustness, scalability, and reliability. - Develop and maintain cloud-native, multi-tenant SaaS applications with high availability. - Stay current with emerging AI technologies, cloud frameworks, and integration patterns. - Support CI/CD pipelines, containerized deployments, and infrastructure-as-code practices. Requirements - 10+ years of experience in building cloud-based, distributed applications. - Strong experience with AI technologies, including LLMs, RAG, LangChain, and LlamaIndex. - Expertise in Python and Java, including NLP libraries (spaCy, NLTK, Hugging Face Transformers). - Hands-on experience with model deployment frameworks (TensorFlow Serving, MLflow, Kubernetes). - Proficiency in cloud platforms (AWS, Azure) and services for AI/ML integration. - Experience with microservices, SaaS architectures, data pipelines, and top-tier datastores (MongoDB, SQL Server, MySQL). - Strong understanding of Linux, Docker, Kubernetes, Apache Tomcat, Nginx, and CI/CD tools. - Familiarity with security best practices in cloud/distributed systems and infrastructure as code (Terraform, CloudFormation). - Excellent problem-solving, debugging, and analytical skills. - Strong communication skills in English (C1 level) and ability to work effectively in a remote, distributed team environment. Benefits - Competitive salary and performance incentives. - Fully remote, flexible work environment. - Career growth, mentorship, and access to cutting-edge AI technologies. - Collaborative, high-performance team culture with focus on innovation. - Health insurance and standard employee benefits. - Opportunities to work on industry-leading AI platforms with global impact. A talent matching platform partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When applying, your profile undergoes an AI-powered screening process designed to identify top talent efficiently and fairly. The AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. It compares your profile to the job's core requirements and past success factors to determine your match score. Based on this analysis, the top 3 candidates with the highest match are automatically shortlisted. When necessary, a human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, it is shared directly with the company that owns the job opening. The final decision and next steps are then made by their internal hiring team.