Job purpose
We are looking for an enthusiastic Software Engineer to help build modern applications, internal tools, and automation systems that increasingly leverage AI capabilities.
You will work primarily as a software engineer — designing APIs, building services, improving system reliability — while also integrating AI models into real features that improve productivity and user experience.
This role is ideal for someone who is strong in software engineering and excited to apply AI in practical, production‑ready ways. A successful candidate will develop and enhance a large-scale micro services system. Candidates should expect to work with other team members on designing and implementing core platform components. Candidates should also expect to create unit tests, automated functional tests and load tests for all micro services.
Duties and responsibilities
- Design, build, and maintain backend services, APIs, and internal tools.
- Develop clean, maintainable, and well‑tested code in Python, Node.js/TypeScript, or Go.
- Work with databases, message queues, and cloud infrastructure.
- Participate in code reviews, architecture discussions, and sprint planning.
- Improve system reliability, performance, and observability.
- Help evaluate AI tools, libraries, and model options.
- Collaborate with senior engineers on prompt design and AI workflow improvements.
- Ensure AI usage follows basic governance and data‑handling guidelines.
- Work closely with product managers to translate requirements into technical solutions.
- Collaborate with AI engineers, architects, and DevOps teams.
- Contribute to documentation, internal knowledge sharing, and continuous improvement.
Capabilities
- 2–5 years of experience in software engineering.
- Strong skills in Python , Node.js/TypeScript , or Go .
- Experience building APIs, microservices, or backend systems.
- Familiarity with relational and NoSQL databases.
- Understanding of cloud platforms (AWS/GCP/Azure) and CI/CD pipelines.
- Good debugging, testing, and problem‑solving skills.
- Experience with Message Broker systems (RabbitMQ, Kafka, Pub/Sub).
- Experience with containerization (Docker, Kubernetes).
- Experience calling LLM APIs (OpenAI, Anthropic, Google).
- Basic understanding of prompt engineering.
- Understanding of how to integrate AI features into applications.
- Curiosity and willingness to learn new technologies.
- Strong communication and collaboration skills.