Senior Full Stack AI and Data Engineer

**Candidate must be willing to go into office 3 days a week**Senior Full-Stack AI & Data Engineer – ContractRBA is an established leader and trusted partner for enterprise and mid-size organizations seeking to transform their business through technology solutions. As a Digital and Technology consultancy, we combine strategic insight with technical expertise to deliver impactful, scalable solutions that align with business goals. We take pride in working with some of the most recognized companies in our market—while fostering a culture that blends challenging career opportunities with a collaborative, fun work environment.We are seeking a Senior Full-Stack AI & Data Engineer to join our growing Data & AI practice, supporting a high-impact client. In this role, you will lead the design and development of end-to-end AI-powered applications that drive personalization, predictive analytics, and next-generation digital experiences.You’ll partner with business stakeholders, product teams, and engineers to build production-grade AI solutions—from data pipelines and model development to APIs and user-facing applications. The ideal candidate brings deep expertise across the full stack, modern data platforms, and generative AI technologies, with a passion for solving complex business challenges through innovative solutions.ResponsibilitiesDesign and develop end-to-end AI-powered applications, including backend APIs and user-facing interfaces, to enable scalable and intuitive AI solutions.Build and maintain robust APIs using technologies such as Node.js, NestJS, or FastAPI, and develop modern web applications using React or similar frameworks.Develop, fine-tune, and deploy machine learning models using frameworks such as PyTorch and Scikit-learn.Implement advanced generative AI solutions, including Retrieval-Augmented Generation (RAG) pipelines and multi-modal AI applications.Design and build agentic AI systems using frameworks such as LangChain, enabling multi-step reasoning, tool use, and automation.Architect and optimize end-to-end data pipelines (ETL/ELT) using Python, SQL, and orchestration tools such as Airflow.Manage and integrate data workflows within Snowflake, leveraging technologies such as Snowpark or Cortex.Implement monitoring and observability for AI systems, including tracking model performance, drift, latency, and reliability.Design and deploy cloud-native solutions using Docker, Kubernetes, and CI/CD pipelines across AWS, Azure, or GCP.Collaborate with business stakeholders to translate data into actionable insights and intelligent applications.Contribute to DevOps best practices, including infrastructure-as-code (Terraform) and automated testing.Mentor junior engineers and promote best practices in AI ethics, data governance, and code quality.RequirementsBachelor’s or Master’s degree in Computer Science, Engineering, or related field.5+ years of experience across full-stack development, including backend (Node.js/Python) and frontend frameworks (React or similar).Strong experience designing and building data pipelines and modern data platforms, including expertise in SQL and data modeling.Proven experience deploying AI/ML solutions in production environments, including MLOps and model lifecycle management.Hands-on experience with generative AI technologies, including LLMs, prompt engineering, and RAG architectures.Experience with cloud platforms such as AWS, Azure, or GCP.Strong understanding of DevOps practices, including CI/CD, containerization, and infrastructure-as-code (Terraform).Excellent communication skills and ability to work effectively in client-facing environments.Preferred QualificationsExperience with Snowflake, including Snowpark, Cortex, or similar data platform capabilities.Experience building agent-based AI systems or working with frameworks such as LangChain.Familiarity with vector databases and semantic search architectures.Experience developing mobile applications using React Native or Flutter.Knowledge of mobile architecture, UI/UX principles, and API integration patterns.Experience deploying applications to Apple App Store or Google Play Store.Familiarity with security and authentication protocols, including OAuth2, biometric authentication, and secure data handling.Cloud or data platform certifications (AWS, Azure, GCP, Snowflake, or similar).Leadership & CultureDemonstrate leadership through mentorship, technical guidance, and promoting engineering best practices.Balance innovation with pragmatism—able to work across cutting-edge AI solutions and foundational data engineering tasks.Thrive in a collaborative, fast-paced consulting environment with a strong focus on client impact and delivery excellence.