MLOps / AI DevOps Engineer

Job Overview

The Backend Developer will design, develop, and maintain scalable backend systems and APIs supporting AI-driven applications. This role demands strong proficiency in Python, FastAPI, and microservices architecture, with additional exposure to MCP servers, real-time streaming (LiveKit), and parallel data processing. The developer will collaborate with AI/ML teams to build highly performant APIs, integrate live video/audio/text streaming, and maintain deployment pipelines optimized for AI workloads.

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Key Responsibilities

• Design and develop backend services and REST APIs using FastAPI and microservice-based architectures.

• Implement and manage authentication, authorization, and integration testing.

• Build, deploy, and maintain MCP servers for AI application backends.

• Enable real-time text, video, and audio streaming using LiveKit or similar frameworks.

• Implement parallel processing pipelines using Airflow, Celery, or equivalent tools.

• Integrate Elasticsearch for indexing, search, and performance optimization.

• Collaborate with AI and ML teams to connect deployed models to application backends.

• Manage and optimize CI/CD pipelines, ensuring stable releases and automated testing.

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Required Skills & Qualifications

• Strong hands-on expertise in Python and frameworks such as FastAPI, Flask, or Django REST Framework.

• Proven experience in designing and maintaining microservices-based architectures.

• Knowledge of API design, versioning, and secure data exchange protocols.

• Practical experience in MCP server setup and backend integration with AI services.

• Familiarity with Airflow, Celery, or distributed task orchestration systems.

• Experience working with Elasticsearch, PostgreSQL, or similar databases.

• Proficiency in CI/CD tools (GitHub Actions, Jenkins, or GitLab CI) and version control (Git).

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Preferred (Good to Have)

• Experience with Linux-based deployment and shell scripting for server management.

• Exposure to GPU-based coding and parallel computation for high-performance tasks.

• Knowledge of NLP, Vision, Text-to-Voice, and multimodal systems integration.

• Experience with containerization (Docker) and orchestration (Kubernetes) for scalable deployments.

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Soft Skills

• Strong analytical and debugging skills for backend and infrastructure-level issues.

• Excellent communication and documentation abilities.

• Collaborative and proactive approach when working with AI Research, ML, and Integration teams.

• Eagerness to explore cutting-edge backend, streaming, and AI integration technologies.