AI Software Engineer

CapsLock

1d•Remote

About The Position

CapsLock is a dynamic, global IT marketing company that pioneers unique, scalable customer acquisition solutions for B2C clients. We combine deep expertise in IT, design, and data analytics, enabling us to tackle the most complex sales challenges across a wide range of industries—primarily for large North American partners. By seamlessly integrating digital marketing services, AI-based predictive analytics, proprietary MarTech products, and sales consulting, we deliver powerful, data-informed customer acquisition solutions. This role offers a unique opportunity to work at the forefront of generative AI integration and product development. Reporting directly to our IT Director, you will be the primary catalyst driving our company's AI transformation, identifying cutting-edge opportunities, and architecting autonomous AI agents. You'll be in charge in shaping AI-powered solutions while collaborating with a skilled technical team (Development, DevOps, Design and QA). If you're passionate about applying generative AI technologies and creating innovative products, this position provides an exciting platform for your expertise and creativity.

Requirements

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
Existing experience in developing and implementing solutions based on generative AI models.
Proven track record of developing functional AI agents and identifying transformation opportunities.
Proficiency in any programming language. Experience with modern AI stacks (e.g., Python, TypeScript) is highly preferred.
Familiarity with existing AI providers (OpenAI, Google, Anthropic, xAI, etc.).
Understanding of modern Image generation models (e.g., Stable Diffusion, DALL-E 3, Adobe Firefly) and Video generation models (e.g., Runway Gen-3, Pika Labs, OpenAI Sora, Google Veo).
Hands-on experience with Agentic frameworks (e.g., LangChain, AutoGen) and RAG.
Excellent analytical and problem-solving skills.
Strong communication and collaboration skills to work effectively with cross-functional teams.
Fluent in English language.

Nice To Haves

Experience with project management Agile methodologies such as Kanban or Scrum.
Knowledge of AI ethics and techniques to mitigate bias in AI models.
Master's or Ph.D. in Computer Science.
Familiarity with cloud-native architectures and container orchestration (e.g., Kubernetes, Docker).

Responsibilities

Develop AI Agents Architect, build, and deploy autonomous and semi-autonomous AI agents to streamline complex workflows.
Integrate generative AI Providers. Combine different AI solutions and providers to create comprehensive and efficient AI systems.
Design and implement architecture. Design and contribute to the architecture of AI systems, ensuring scalability, reliability, and performance.
Designing data structures and data management. Collect, preprocess, and analyze data to ensure high-quality inputs for AI models.
Write surrounding code. Develop the necessary code to support AI models, ensuring seamless integration with existing systems and infrastructure.
Monitor, maintain and optimize solutions. Continuously monitor the performance of AI products and systems, making necessary adjustments to improve accuracy and efficiency.
Directly collaborate with multiple departments in our company. Work closely with engineers, product managers, and other stakeholders to identify business problems and develop AI-driven solutions.
Create technical documentation. Produce comprehensive technical documentation for AI systems, including system architecture, model specifications, data flows, and testing procedures.
Develop Quality Assurance procedures. Create and implement QA processes specifically tailored for AI systems, including data validation, model testing, and performance evaluation.
Stay updated. Keep abreast of the latest AI technologies, trends, and best practices to ensure the company remains at the forefront of AI innovation.
Security Awareness. Understanding of security best practices in AI system development and deployment.