BIMCAP

BIMCAP Private Limited BIMCAP is an international BIM outsourcing company with an expanding portfolio of cultural, infrastructure, and commercial projects around the world. We are leaders in BIM innovation, growth of BIM talents, and unique for our supportive family-like culture that expanded from Hong Kong to Netherlands, England, Germany, Hungary, Spain, and Philippines. This role is based out of Bhilai, Chhattisgarh, for BIMCAP’s subsidiary company registered as Ecliptiko Private Limited . Job Summary We are looking for a driven and curious AI Engineer with hands-on experience in Large Language Models (LLMs). In this role, you’ll work on end-to-end development and deployment of LLM-based solutions, including prompt engineering, model fine-tuning, and cloud-based deployment. You’ll collaborate closely with product and engineering teams to build intelligent, scalable, and secure AI-powered systems. Key Responsibilities Design, develop, and optimize prompt strategies for LLM-based applications. Fine-tune pre-trained models (e.g., OpenAI, Hugging Face, etc.) using custom datasets. Build and deploy LLM-powered APIs and services in cloud environments (AWS, GCP, or Azure). Integrate LLMs into applications with efficient inference and cost-aware strategies. Conduct evaluations, benchmarking, and A/B testing for LLM outputs. Collaborate on data collection, preprocessing, and feature engineering tasks. Stay up to date with the latest in GenAI research and toolchains. Requirements 2+ years of industry experience in AI/ML or related fields. Strong grasp of NLP concepts, transformers, and recent LLM developments. Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or similar). Experience with prompt engineering and prompt evaluation. Hands-on experience with cloud platforms (AWS/GCP/Azure), Docker, and CI/CD. Familiarity with APIs and SDKs of major LLM providers (e.g., OpenAI, Cohere, Anthropic). Understanding of data privacy, security, and ethical considerations in AI. Preferred Qualifications Experience with tools like LangChain, LlamaIndex, or Vector DBs (e.g., FAISS, Pinecone). Exposure to Retrieval-Augmented Generation (RAG) systems. Knowledge of MLOps best practices and ML model lifecycle management

Job Summary: We are seeking an experienced DevOps Engineer with a strong background in deploying and managing AI applications on Azure. The ideal candidate should have experience in deploying AI systems, understands AI Agentic architectures, and can optimize and manage LLM-based applications in production environments. Key Responsibilities: Deploy, scale, and monitor AI applications on Microsoft Azure (AKS, Azure Functions, App Services, etc.). Build and optimize AI Agentic systems for robust and efficient performance. Implement CI/CD pipelines for seamless updates and deployments. Manage containerized services using Docker/Kubernetes. Monitor infrastructure cost, performance, and uptime. Collaborate with AI engineers to understand application requirements and support smooth deployment. Ensure compliance with data security and privacy standards. Requirements: 2+ years of experience in deploying and managing AI/ML applications. Proficiency in Azure cloud services and DevOps practices. Familiarity with LLM-based systems, LangChain, Vector DBs, and Python. Experience with containerization tools (Docker) and orchestration (Kubernetes). Understanding of AI system architecture, including Agentic workflows. Strong problem-solving and optimization skills. Preferred Qualifications: Experience with Gemini, OpenAI, Anthropic, or Hugging Face APIs. Familiarity with LangChain, LlamaIndex, or ChromaDB. Prior experience in managing high-availability, secure, and cost-optimized AI deployments.

Job Summary: We are seeking an experienced DevOps Engineer with a strong background in deploying and managing AI applications on Azure . The ideal candidate should have experience in deploying AI systems, understands AI Agentic architectures, and can optimize and manage LLM-based applications in production environments. Key Responsibilities: Deploy, scale, and monitor AI applications on Microsoft Azure (AKS, Azure Functions, App Services, etc.). Build and optimize AI Agentic systems for robust and efficient performance. Implement CI/CD pipelines for seamless updates and deployments. Manage containerized services using Docker/Kubernetes. Monitor infrastructure cost, performance, and uptime. Collaborate with AI engineers to understand application requirements and support smooth deployment. Ensure compliance with data security and privacy standards. Requirements: 2+ years of experience in deploying and managing AI/ML applications. Proficiency in Azure cloud services and DevOps practices. Familiarity with LLM-based systems, LangChain, Vector DBs, and Python. Experience with containerization tools (Docker) and orchestration (Kubernetes). Understanding of AI system architecture, including Agentic workflows. Strong problem-solving and optimization skills. Preferred Qualifications: Knowledge and experience with Microsoft Azure Experience with Gemini, OpenAI, Anthropic, or Hugging Face APIs. Familiarity with LangChain, LlamaIndex, or ChromaDB. Prior experience in managing high-availability, secure, and cost-optimized AI deployments.