Job title: engineering manager cinc systems, the leading provider of accounting and management software in the community association management industry, is seeking a highly skilled engineering manager to lead their engineering efforts in colombia. - the ideal candidate will be responsible for leading backend design and development of enterprise saas products using node.js and express.js, adhering to clean architecture and solid principles. - key responsibilities include mentoring backend developers, establishing coding best practices, and ensuring adherence to security and scalability standards. - collaboration with cross-functional teams, including product, qa, and devops teams, is essential in an agile environment to manage restful apis lifecycle and integrate with aws services. requirements: - 10+ years of backend development experience in enterprise saas environments. - strong proficiency in node.js and express.js. - advanced experience with ms sql server and mongodb. bonus points: - fluency in english (written and spoken). - familiarity with ci/cd tools like jira, bitbucket, and confluence. - experience with aws services, docker, and infrastructure automation knowledge. this role requires a highly skilled professional who can effectively communicate with cross-functional teams and drive product development forward while ensuring customer satisfaction....
Agile innovation is a pioneering force in software development, creating groundbreaking solutions for leading brands and startups across various sectors. job opportunity as an ai expert at our company, you will play a crucial role in designing and deploying cutting-edge agentic pipelines for energy data, building and fine-tuning large language model (llm) applications, and developing models for contract intelligence, price forecasting, and energy portfolio optimization. you will work on delivering scalable apis and ai services using advanced frameworks, integrate with cloud-native platforms, and modern data infrastructure. additionally, you will mentor peers and contribute to best practices in applied ai and ml engineering. key requirements - 7+ years of professional software development experience - 5+ years deploying machine learning systems in production - 3+ years building with llms, both locally-hosted and api-based - expertise in python and libraries like pytorch, tensorflow, and hugging face - hands-on experience with agentic pipelines, rag, vector search, and prompt engineering - deep familiarity with cloud platforms (aws, gcp, azure) and tools like docker, kubernetes - experience designing scalable microservices and rest apis for ai inference workflows - excellent verbal and written communication skills - systems-level thinking with a product mindset - upper-intermediate english level bonus skills - experience in an early-stage startup environment - experience in energy, sustainability, or infrastructure tech - a commitment to ethical, socially responsible a...
Lead ai engineer we are looking for a visionary and experienced technology leader to spearhead the development, deployment, and optimization of our artificial intelligence platforms. this role is part of an innovative project with international collaboration and cutting-edge technology. spearhead the design, deployment, and scaling of ai systems in production environments. create and manage cloud-native infrastructure across aws and azure, focusing on performance, security, and reliability. oversee the full lifecycle of ai systems, including devops/mlops practices, automation, and monitoring. implement infrastructure as code using terraform, containerization with docker, and orchestration via kubernetes. collaborate cross-functionally with data science, engineering, and product teams to ensure systems align with business objectives. evaluate and integrate tools for large language models (llms), including frameworks like llama or similar technologies. requirements 8+ years of experience in engineering roles, with at least 3 years in technical leadership or director-level positions. proven experience deploying ai systems in production environments at scale. deep knowledge of cloud platforms (aws and azure) and cloud-native architectures. strong background in saas environments and distributed systems. expertise in docker, kubernetes, and terraform. solid understanding of devops/mlops pipelines and best practices. familiarity with llms and experience working with related tooling (e.g., llama or similar). excellent communication and leadership skills. minimum c1 level of english...
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