Fullstack AI Engineer

We are seeking a Fullstack AI Engineer to design, build, and deploy innovative AI-powered applications that solve complex business challenges. This role combines hands-on software engineering with client-facing consulting skills, making it ideal for someone who can move seamlessly from solution design to implementation and stakeholder engagement.

The ideal candidate will have strong experience in fullstack development, AI application architecture, and large language model (LLM) solutions, along with the ability to translate business needs into scalable technical outcomes.

Key Responsibilities

• Design, develop, and maintain fullstack AI applications using Python, SQL, and modern development frameworks
• Build and optimize LLM-powered applications, including prompt workflows, agent orchestration, and production-ready AI features
• Develop and enhance Retrieval-Augmented Generation (RAG) systems using vector databases and semantic search
• Integrate and orchestrate APIs across internal and third-party platforms
• Deploy and manage applications in cloud environments such as AWS, Azure, or Google Cloud
• Build, manage, and optimize containerized solutions using Docker and Kubernetes
• Create and support data engineering workflows and ETL pipelines for AI and analytics applications
• Implement Git-based development workflows and contribute to CI/CD pipelines for efficient software delivery
• Partner with business stakeholders to gather requirements and define solution goals
• Translate business problems into technical architecture and implementation plans
• Lead or support client workshops, demos, and solution walkthroughs
• Develop rapid prototypes and proof-of-concepts to validate ideas and accelerate delivery
• Contribute to solution architecture and system design for scalable, secure, and high-performing AI applications

Qualifications:

• Strong programming experience with Python and SQL
• Experience building AI applications using large language models (LLMs)
• Hands-on experience with RAG systems, vector databases, and semantic search
• Experience with API integration and orchestration
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud
• Experience with Docker and Kubernetes
• Background in data engineering and ETL pipeline development
• Familiarity with Git and CI/CD best practices
• Ability to gather requirements and communicate effectively with both technical and non-technical stakeholders
• Strong written and verbal communication skills

Compensation

About Us

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