Back End Developer AI

We are looking for a seasoned Backend Engineer to lead the development and integration

of AI services within our backend systems for an AI-driven EDA platform. The role focuses

on building scalable APIs, integrating ML models, and ensuring performance, security, and

reliability across services.

Key Responsibilities

• Design and develop robust backend architectures using Node.js (preferred) or

Python (FastAPI, Flask, Django).

• Integrate AI/ML models into production via REST/GraphQL APIs, TensorFlow

Serving, ONNX, or containerized pipelines.

• Build and maintain microservices for real-time and batch AI inference.

• Ensure secure API design, handling OAuth2, JWT, RBAC, and other authentication

and authorization mechanisms.

• Optimize database performance for high-throughput systems using PostgreSQL,

MongoDB, Neo4j (GraphDB), Redis, or Firebase.

• Collaborate with AI/ML engineers to understand model requirements and deliver

low-latency integration pipelines.

• Implement best practices for scalability, fault tolerance, and system

observability.

• Work with DevOps teams to automate deployment via CI/CD pipelines (Jenkins,

GitHub Actions) and manage infrastructure using Docker, Kubernetes, and

Terraform.

Required Skills & Qualifications

• Strong backend programming experience in Node.js (preferred), Python (FastAPI,

Flask, Django), or Java (Spring Boot).

• Proficient in building and scaling RESTful APIs and GraphQL endpoints.

• Experience deploying and integrating AI/ML models into backend systems.

• Proficient in database design and optimization: PostgreSQL, MongoDB, Redis,

Neo4j.

• Experience with cloud platforms such as AWS, GCP, or Azure.

• Working knowledge of containerization and orchestration: Docker, Kubernetes.

• Strong understanding of API security protocols: OAuth2, JWT, RBAC.

• Familiarity with DevOps and CI/CD practices.

• Bachelor's or master's degree in computer science, Engineering, or a related field.

Preferred Experience (Nice to Have)

• Experience with EDA tools or AI-driven design automation platforms.

• Background in real-time interface systems or stream processing.

• Prior work with custom AI pipelines or AI workflow orchestration.