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Liquid ReplyGolang Software Engineer
Golang Software Engineer primarily focused on open source projects to enhance cloud - native development. Work on microservices and Kubernetes alongside clients and internal teams.
About the role
- Lead and contribute to the implementation of complex Java back-end services, ensuring adherence to coding standards, performance, and best practices.
- Design, architect, and implement AI features and models within client applications, with a focus on agentic models and advanced natural language processing.
- Design and architect robust, cost-effective, and scalable cloud-native applications using modern Java frameworks and AWS services.
- Demonstrate deep expertise in various core AWS services (e.g., EC2, Lambda, EKS) and key AWS AI services (e.g., Amazon Bedrock, SageMaker, Comprehend) and their optimal use within a Java ecosystem.
- Integrate AI components, LLMs, and large datasets using Python scripting and Java application logic, ensuring reliable data pipelines and API connectivity.
- Engage with clients to understand their business requirements and identify high-impact use cases for AI/ML and generative AI, providing commercial experience-backed advice on project feasibility and ROI.
- Promote and implement DevOps principles (CI/CD, Infrastructure as Code) to automate deployment and management of Java applications and AI models on AWS.
- Define and promote Java development, cloud architecture, and responsible AI best practices within client organizations.
Requirements
- Proven mastery of the Java ecosystem for enterprise-level applications, including deep knowledge of modern frameworks like Spring Boot/Spring. (7+ years of relevant experience is essential).
- Proven experience designing, deploying, and managing complex solutions within the AWS cloud environment.
- Hands-on experience developing and integrating AI models into production applications. Knowledge of agentic model frameworks and principles is a strong plus.
- Proficiency in Python scripting for data manipulation, model interaction, and API integration.
- Proven experience contributing to or leading commercial AI projects, understanding the full lifecycle from proof-of-concept to production deployment.
- In-depth, hands-on knowledge of core AWS services and specific AI services like Amazon Bedrock or SageMaker.
- Proven experience in a consulting role, with a strong focus on client satisfaction and delivering practical outcomes.
- Ability to effectively communicate complex technical, architectural, and AI concepts to diverse technical and business audiences.
- AWS certifications (e.g., AWS Solutions Architect Professional, AWS Machine Learning Specialty) are highly desirable.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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