Backend Engineer

5+ years of experience in backend engineering, with at least 2 years leading teams or projects. Proven expertise in developing APIs and backend services using Python and FastAPI. Hands-on experience with generative AI applications, including model integration and deployment. Technical Skills: Strong proficiency in AWS cloud platform and services like Lambda, ECS, S3, or equivalent. Azure or GCP may be acceptable. Expertise in database design and optimization (SQL and NoSQL databases). Experience with containerization tools (e.g., Docker) and orchestration frameworks (e.g., Kubernetes). Familiarity with CI/CD pipelines and IaC tools like Terraform or CloudFormation. Soft Skills: Strong problem-solving abilities and attention to detail. Excellent communication and leadership skills, with the ability to collaborate across teams. Ability to prioritize and manage multiple projects effectively. Education: Bachelor s or Master s degree in Computer Science, Engineering, or a related field.

Reporting and Coordination

For the provision of staff augmentation services, the Agency Personnel will take instructions from the Manager at the Information

Technology Department at ADB and work closely with the project team, internal and external stakeholders.

The Agency Personnel will provide any other services as required by the team and ADB ITD supervisor or user unit.

Work Arrangement

Hybrid, requiring employees to report onsite three times a week. If the user unit requires contractors to report to HQ, compliance is

mandatory.

Work Schedule is from 8:00AM 5:00PM Manila Time.

1. Technical Leadership:

Support the design, development, and optimization of backend services and APIs using Python and FastAPI.

Provide architectural support for systems integrating with generative AI models and services.

Ensure high performance, scalability, and reliability of backend systems.

2. Generative AI Integration:

Collaborate with data scientists and ML engineers to deploy generative AI models in production.

Build and optimize APIs for AI model inference, including managing input/output pipelines for real-time and batch

processing.

Implement features such as caching, load balancing, and vector search to enhance AI system performance.

3. Cloud Infrastructure Management:

Architect and maintain backend systems on cloud platforms (AWS, Azure, or GCP).

Leverage cloud-native services to ensure secure, scalable, and cost-effective infrastructure.

Manage deployment pipelines using containerization (Docker) and orchestration tools (Kubernetes).

4. Team Collaboration:

Collaborate with the team of backend engineers, fostering a culture of collaboration, innovation, and technical

excellence.

Work closely with the frontend, DevOps, and product teams to align backend development with business goals.

Conduct code reviews and ensure adherence to best practices.

5. Performance Monitoring & Optimization:

Monitor backend systems for performance, reliability, and scalability.

Optimize database queries, API response times, and resource utilization.

Implement robust logging, monitoring, and ing systems.

6. Emerging Technology Adoption:

Stay updated with advancements in backend technologies, generative AI, and cloud computing.

Recommend and integrate new tools and frameworks to improve system capabilities..