Back End Developer

About the Role

We are seeking a Backend Developer (AI/ML Integration) who will work at the intersection of backend engineering, data-driven automation, and AI/ML enablement. The ideal candidate will have a strong foundation in backend systems, data structures, and algorithms, along with practical experience integrating machine learning models and AI-driven automation workflows.

You will design scalable backend services, integrate AI models (including LLMs such as GPT-5), develop APIs, and deploy intelligent microservices powering automation, analytics, and enterprise knowledge platforms.

Key Responsibilities

Backend Engineering & API Development

• Design, develop, and maintain scalable backend services and RESTful APIs.
• Build microservice-based solutions ensuring performance, reliability, and scalability.
• Participate in code reviews, debugging, and production performance tuning.

AI/ML & LLM Integration

• Integrate AI/ML and LLM models (e.g., GPT-5, fine-tuned/custom models) into backend workflows.
• Develop and deploy ML/NLP models for automation, predictive analytics, and intelligent knowledge retrieval.
• Customize and optimize AI plugins for automation, analytics, and insights.

ML Pipelines & MLOps

• Build and maintain end-to-end ML pipelines for training, testing, and deployment.
• Use MLOps tools (MLflow, Kubeflow, DVC) for experiment tracking and model lifecycle management.
• Work with vector databases (Pinecone, Weaviate, FAISS, Milvus) to build AI-driven search/retrieval systems.

Cloud, DevOps & Automation

• Work with cloud platforms (AWS, Azure, GCP) for deployment and infrastructure management.
• Implement CI/CD pipelines for automated deployment and monitoring.
• Use automation/orchestration tools like Airflow or Prefect for workflow automation.
• Work with containerization & orchestration tools (Docker, Kubernetes).
• Ensure data security, compliance, and scalability across all deployments.

Required Skills & Qualifications

Core Technical Skills

• Strong programming expertise in Java and Python.
• Excellent understanding of data structures, algorithms, and software design principles.
• Hands-on experience with AI/ML frameworks: TensorFlow, PyTorch, Hugging Face.
• Proficiency in NLP/LLM integration, including LangChain, RAG, OpenAI APIs, and Anthropic models.
• Experience with backend frameworks and microservice architectures.

Cloud & DevOps

• Familiarity with AWS cloud infrastructure and Terraform (IaC).
• Working knowledge of Docker, Kubernetes, and CI/CD workflows.

AI Infrastructure

• Experience with vector databases (Pinecone, Weaviate, FAISS, Milvus).
• Understanding of MLOps tools such as MLflow, Kubeflow, or DVC.

Nice to Have

• Internship or project experience in AI/LLM integration or backend automation.
• Experience with API security, authentication, and scalable system architecture.
• Exposure to RAG frameworks and chatbot tools: Rasa, Dialogflow, Botpress.
• Contributions to open-source AI/automation projects.