The role of AI Architect involves designing and implementing artificial intelligence systems to drive business growth. Key Responsibilities - Design and Implement AI Systems: Develop AI system blueprints from data ingestion to inference services, considering scalability and reliability. - Architect Pipelines: Specify and oversee the construction of end-to-end LLM/ML pipelines for structured and unstructured energy data, ensuring seamless integration with existing infrastructure. - Vector Search and Knowledge Graphs: Define strategies for retrieval-augmented generation, vector databases, and knowledge graphs to power contract intelligence, enabling data-driven decision-making. - Model Development and Deployment: Guide teams in building models for contract auditing, price forecasting, and portfolio optimization, and design strategies for end-to-end deployment into production, including service hosting, containerization, and cloud infrastructure. - Coding Standards and Review Processes: Establish coding standards, testing frameworks, and review processes for AI/ML workflows, ensuring consistency and quality. - Mentorship and Leadership: Coach engineers in applied AI, review design documents, and present architecture reviews to stakeholders, including C-suite, driving project success. Requirements - 8+ years of professional software development experience, with 5+ years in production ML/AI systems; - Proven track record as an AI Architect or technical lead, able to envision complex systems and drive them to production; - Demonstrated experience in AI research & development; - Publishing, prototyping novel approaches, or leading R&D; projects; - Proven experience building with LLMs (locally hosted and API-based), plus hands-on RAG/vector search experience; - Fluent in designing microservices and REST APIs for AI inference at scale; - Strong systems-level thinking and product mindset, able to balance research and engineering trade-offs; - Experience with cloud-native platforms (AWS, GCP, Azure), Docker, and Kubernetes; - Excellent verbal and written communication; - Comfortable presenting to executive audiences; - Upper-Intermediate English level. Preferred Qualifications - Early-stage startup experience, especially shaping nascent AI products; - Domain experience in energy, sustainability, or industrial infrastructure; - Thought-leadership in AI/ML: open-source contributions, publications, or conference talks; - Commitment to ethical, socially responsible AI. What We Offer - Professional Growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps; - Competitive Compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities; - Exciting Projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands; - Flexibility: Tailor your schedule for an optimal work-life balance by having the options of working from home and going to the office – whatever makes you the happiest and most productive.