Full Stack Engineer, Agentic AI

Join a remote-first digital product engineering team building innovative, AI-powered applications for ambitious startups, established brands, and enterprise clients. In this role, you will combine full-stack engineering expertise with generative AI, large language models (LLMs), and agentic workflows to transform complex business challenges into production-ready solutions. You will work across the entire development lifecycle, from understanding client needs and designing technical architectures to deploying, testing, and optimizing scalable applications. Collaborating with experienced engineers, designers, and cross-functional teams, you will help deliver intelligent products that create measurable business value. The position offers exposure to diverse industries, modern technology stacks, and emerging AI capabilities. If you thrive in autonomous environments, enjoy solving challenging problems, and want to shape the next generation of AI-driven products, this opportunity offers meaningful technical ownership and continuous learning.

• Professional experience: Approximately 4–6 years of experience as a Full Stack Engineer, with a proven track record of delivering and maintaining production software across the stack.

• Programming expertise: Strong experience with TypeScript and modern web technologies, including React and Node.js, alongside proficiency in Python or Go.

• Generative AI experience: Practical experience building AI-powered applications and integrating LLMs into production workflows. Familiarity with image or video generation is an advantage.

• LLM infrastructure: Experience hosting, tuning, and managing LLM services, libraries, or tools, with an understanding of model selection, performance optimization, and production deployment.

• Agentic workflows: Experience designing, building, and using agentic systems, including creating or integrating MCP servers and connecting models with external tools and services.

• AI application development: Demonstrated experience delivering AI-driven features such as chatbots, intelligent search, information extraction, document construction, or automated data transformation.

• Prompt engineering and experimentation: Familiarity with prompt design, structured experimentation, evaluation methodologies, and iterative improvement of model outputs.

• Model customization: Experience fine-tuning large language models using open-source models or commercial services.

• Testing and reliability: Confidence in establishing testing infrastructure for AI applications, validating agent behavior, and addressing the reliability challenges associated with non-deterministic model outputs.

• Cloud and data platforms: Experience with at least one major cloud provider, such as AWS, Google Cloud Platform, or Microsoft Azure, particularly data and machine learning services such as BigQuery or SageMaker.

• Consulting and client management: Previous experience in consulting, contracting, or client-facing engineering roles, with the ability to manage expectations, communicate progress, and deliver against project timelines.

• Adaptability and ownership: Comfortable working autonomously in a fast-moving environment, navigating ambiguity, learning unfamiliar technologies, and adapting to different client requirements and technical stacks.

• Communication and collaboration: Strong problem-solving skills and the ability to explain technical decisions clearly while collaborating with engineers, designers, and business stakeholders.

Additional experience that would be beneficial includes:

• Kubernetes, Docker, and container orchestration.

• ETL frameworks and data pipeline tools, such as Apache Airflow.

• Mobile application development using React Native or native iOS and Android technologies.

• Strong product design sensibility and user experience intuition.

• Statistics, data science, or advanced analytical techniques for intelligent data processing.

• Relevant technical certifications, open-source contributions, or published technical work.