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.