Role Description We are seeking a highly skilled AI & Software Solutions Architect with experience in developing complex software solutions for big data processing and high-load environments, to define and lead the end-to-end architecture for our enterprise platform. You will actively participate in discovery phases and design and guide the implementation of end-to-end solutions that combine data and cloud services. This role is instrumental in shaping our AI architecture strategy, driving automation with intelligent agent systems, and modernizing enterprise software workflows. - Define the end-to-end architecture for our platform, owning the reference architectures, guardrails, and roadmaps for secure, high-load big data processing and AI capabilities (LLMs, agentic applications) across multiple clouds. - Bridge the gap between business and tech, working with stakeholders and engineering teams to build scalable, secure architectures aligned with business goals. Qualifications - 5+ years building and running production systems — not only demos and POCs. - Strong understanding of software development methodologies and practices, including Agile and DevOps. - Hands-on experience building production LLM-based applications and agentic workflows. - Extensive experience with cloud platforms. Prior experience with AWS is a plus. - Understanding of modern backend stacks (NodeJS/Python) and experience with legacy migration (PHP) is a benefit. - Experience with database design and management (SQL, NoSQL). - Strong understanding of software architecture patterns, including microservices, event-driven architecture (EDA), CQRS (Command Query Responsibility Segregation), and Domain-Driven Design (DDD). - Hands-on experience designing and implementing event streaming systems using Apache Kafka, RabbitMQ, or similar brokers. - Familiarity with Data Lakehouse architecture, including concepts like Delta Lake, Apache Iceberg, or similar table formats. - Proficiency in documenting and visualizing system designs using various tools and approaches. - Familiarity with hybrid search approaches (vector + full-text BM25/Elasticsearch). - Strong query optimization skills across SQL and NoSQL databases (indexing, partitioning, query plans). - Experience integrating LLMs into production systems — RAG pipelines, function calling, AI agent patterns. - Certifications such as AWS Certified Solutions Architect, SEI, SAFE, and Claude Code Certifications nice to have. Requirements - Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. - Already using AI tools in your daily workflow (Claude Code, Copilot, or similar). - Proactive and self-directed; you own outcomes end-to-end and spot problems before they're handed to you. - Excellent communication and interpersonal skills, with the ability to collaborate effectively with technical and non-technical stakeholders. - Strong problem-solving skills and the ability to think strategically. - B2+ English, comfortable collaborating across distributed, multicultural teams. Benefits - Competitive salary tailored to the candidate's experience and skills. Payments are processed monthly (USD). - Full Remote, Work schedule: Monday-Friday, from 1:00 pm to 9:00 pm EEST (incl. 60-min breaks). - Opportunity to work with cutting-edge AI and cloud solutions. - Access to the latest AI tools and premium subscriptions. - Long-term B2B collaboration. - Paid sick leave, vacation, and public holidays. - Reduced Fridays during the summer. Company Description INFUSE is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy .

• Own the architecture and evolution of MANSCAPED’s Snowflake environment • Establish and enforce data modeling standards across core business domains • Design schemas, datasets, and views that support BI, analytics, reporting, and AI use cases • Develop and maintain complex SQL queries, stored procedures, and performance-optimized data structures • Optimize Snowflake performance, warehouse utilization, and cost management • Approve schema changes, RBAC changes, Snowflake architecture changes, and material pipeline modifications • Define and implement the enterprise RBAC model within Snowflake across business functions • Partner with Technology, Infrastructure, Security teams and Analytics stakeholders • Establish standards for row-level security, masking policies, PII handling, and permission-aware data availability • Proactively surface risks related to access, governance, data quality, and warehouse spend • Design and oversee data pipeline architecture standards • Serve as the Analytics-side technical lead for ETL/ELT requirements

• Conduzir discovery técnico com clientes e traduzir necessidades de negócio em arquitetura e propostas executáveis pelo delivery; • Desenhar e defender soluções de migração para AWS (7 Rs), mapeando dependências, planejando ondas e antecipando janelas de cutover; • Projetar Landing Zones (multi-conta, conectividade VPN/Direct Connect, identidade, guardrails de compliance) e estratégias de Disaster Recovery com clareza de RTO/RPO; • Conduzir reuniões executivas e técnicas, adaptando a linguagem à audiência; • Produzir artefatos (escopo, arquitetura, premissas, estimativas) para propostas, com foco em entregas iterativas; • Estimar esforço e custos de migração, antecipando riscos críticos; • Trabalhar próximo ao time de vendas sem perder a voz técnica, sinalizando inviabilidades antes de comprometer prazos.

• Lead architecture, design, and implementation of enterprise-scale technology solutions. • Conduct business and technical discovery sessions with stakeholders to identify requirements and solution strategies. • Develop solution architectures supporting cloud-native, hybrid, and enterprise application environments. • Provide technical leadership throughout the full software development lifecycle, from planning and design through deployment and support. • Evaluate emerging technologies and provide recommendations regarding adoption of new tools, platforms, and methodologies. • Support modernization initiatives involving cloud engineering, containerization, microservices, DevSecOps, and platform automation. • Design solutions utilizing multiple data stores, including relational and NoSQL technologies. • Develop architecture standards, interface standards, performance standards, and quality assurance practices. • Support implementation of enterprise data architecture, data governance, and metadata management strategies. • Provide guidance regarding data integration, data conversion, and enterprise information architecture initiatives. • Collaborate with development, infrastructure, cybersecurity, and business teams to ensure successful solution delivery. • Present technical recommendations, roadmaps, and architecture strategies to executive leadership and stakeholders. • Support implementation of AI and machine learning capabilities where appropriate to enhance mission outcomes.