Agentic AI & Computer Vision Developer

The AI developer should be proficient in building Retrieval-Augmented Generation (RAG) pipelines, fine-tuning and adapting Large Language Models (LLMs), and using orchestration frameworks such as LangChain or LlamaIndex. In addition, the developer must have strong expertise in computer vision (face recognition, ANPR), multimodal AI (connecting text and vision), integration with relational and vector databases, and experience with MLOps tools (Docker, Kubernetes) for scalable deployment.

At least 4 years Bachelors in Software Engineering /IT / Computer Science / Telecom Engineering/AI

Experience: Minimum 2-3 years relevant Experience.

Responsibilities:

• Develop AI-powered solutions including NLP integration with multiple relational databases.
• Design and implement facial recognition and license plate recognition (ANPR) systems.
• Collaborate closely with forensic teams to automate digital evidence classification.
• Develop AI assistants for Client officers enabling querying of records and generation of reports and statistics.
• Build and maintain Retrieval-Augmented Generation (RAG) pipelines.
• Fine-tune and adapt Large Language Models (LLMs) for specific use cases.
• Utilize orchestration frameworks such as LangChain and LangGraph to design and implement AI workflows and pipelines.
• Expertise in multimodal AI combining text and vision modalities.
• Integrate AI solutions with both relational databases and vector databases.
• Use MLOps tools such as Docker and Kubernetes for scalable deployment and management of models and services.
• Develop and expose AI services through modern web frameworks such as FastAPI and Flask to build secure, efficient RESTful APIs.
• Implement and maintain robust API endpoints supporting LangChain and LangGraph orchestration workflows.
• Optimize backend infrastructure for performance, scalability, and security in AI applications.
• Monitor, maintain, and improve existing AI and computer vision models in production.

Additional Desired Skills:

• Experience with cloud platforms (AWS, Azure, GCP) for AI service deployment.
• Knowledge of container orchestration and CI/CD pipelines using tools like Jenkins and GitHub Actions for MLOps workflows.
• Familiarity with GPU acceleration for model training and inference.
• Strong programming skills in Python and relevant AI/ML libraries (TensorFlow, PyTorch, OpenCV).
• Understanding of data privacy, security, and ethical AI development practices.
• Any other Task Given by the Client.
• Provide IT assistance during emergency response operations.

Job Type: Full-time

Work Location: In person