Company overview :
Opportunity with a modernization-tech company helping enterprises transform legacy systems into modern, cloud-native, scalable architectures. We build platforms, accelerators, and automated pipelines that enable engineering teams to migrate, modernize, and deploy faster — with reliability and zero friction.
They are expanding our core engineering team and looking for a Platform Engineer who loves solving deep technical problems and shaping the future of modernization infrastructure.
Role overview
Years of experience : 4- 10 years of experience :
You are the ideal candidate if you have :
- Proven experience in building and deploying large-scale platforms.
- Proficiency in programming languages like Python, Java, JavaScript, or Go.
- Expertise in containerization technologies (e.g., Docker) and infrastructure
orchestration tools.
Strong understanding of distributed systems principles and microservicesarchitecture.
Worked on event-driven architecture using tools like RabbitMQExperience with NoSQL and RDBMSExperience working with APIsWorking knowledge of front-end technologies like ReactExperience with cloud platforms like AWS, Azure, or GCP (familiarity with specific LLM deployment environments a plus).Excellent problem-solving and analytical skills.The ability to work independently and as part of a cross-functional team.A strong passion for innovation and a desire to build impactful solutions.Great code / design skillsAdherence to practices like TDD, Clean Code, Domain-oriented designBonus points for :
Experience working with Large Language Models (LLMs) or other deep learning models.Familiarity with DevOps principles and practices.Experience with security best practices for cloud-based deployments.Experience in building IDE pluginsExperience in extending an open source platformExperience in pipeline orchestration using tools like Airflow or similarWhat would you do here?
In this role, you will :
Design, develop, and deploy robust infrastructure for LLM integration within the Legacy Leap platform.Collaborate with AI Scientists to understand LLM requirements and translate them into scalable and secure platform components.Develop and maintain APIs and services for seamless interaction between theplatform and various LLMs.
Optimize platform performance for efficient handling of LLM workloads.Implement robust monitoring and logging solutions to ensure the health andperformance of the LLM integration layer.
Stay up-to-date on the latest advancements in LLM tools, frameworks, andplatform engineering best practices.
Contribute to developing internal documentation and best practices for LLMplatform operations