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.