Design and build Generative AI applications, including LLM integrations, prompt engineering, and retrieval-augmented generation (RAG) pipelines
Develop clean, efficient, and reusable code across off-the-shelf, semi-custom, and fully custom AI platforms
Integrate AI capabilities into internal systems and customer-facing applications
Evaluate and optimize AI system performance, ensuring accuracy, reliability, and responsible usage
Implement monitoring, logging, and feedback loops for AI systems in production
Collaborate with cross-functional stakeholders to translate business needs into scalable technical solutions
Contribute to system design and architecture with a focus on performance, scalability, and security
Troubleshoot issues, resolve bugs, and support escalated production incidents as needed
Participate in code reviews and promote engineering best practices across the team
Contribute to sprint planning, backlog refinement, and retrospectives to continuously improve team delivery
Document code, systems, and processes to ensure maintainability and knowledge sharing
Demo and communicate solutions effectively to technical and non-technical stakeholders
This role is primarily focused on development (approximately 70–80%), with some responsibility for production support during high-priority or escalated events.

Bachelor’s degree in Computer Science, Information Technology, or equivalent practical experience
Strong programming experience in Python
Experience building and integrating APIs (REST) and testing them using tools such as Postman or similar
Solid experience with Linux environments, including CLI usage, bash scripting, and log analysis
Experience working with cloud platforms such as AWS, GCP, or Azure
Proven experience working with databases and Object-Relational Mapping (ORM) tools
Familiarity with software development best practices, including testing, code reviews, and secure coding
Hands-on experience working with large language models (LLMs), including prompting, API integration, or fine-tuning
Familiarity with retrieval techniques, embeddings, and vector databases
Experience with AI orchestration frameworks
Understanding of model evaluation, hallucination mitigation, and responsible AI practices
Experience with containerization and deployment technologies (e.g., Docker, Kubernetes)
Familiarity with CI/CD pipelines and modern DevOps practices
Experience with observability tools for monitoring and logging distributed systems

Understanding and following Cologix’s information security, cybersecurity, privacy, and environmental management policies, procedures, and standards.
Ensuring conformance with the requirements of both the Information Security Management System (ISMS) and the Environmental Management System (EMS).
Remaining vigilant and reporting any information security or environmental incidents, vulnerabilities, risks, or non-conformities to the appropriate teams.
Actively participating in Cologix’s efforts to maintain and improve information security and environmental performance.

Software Engineer, AI

Key skills