Key Responsibilities :- Design, develop, and deploy AI and machine learning solutions for business applications.- Build and integrate generative AI applications using large language models (LLMs).- Develop AI-powered workflows, intelligent automation solutions, and AI-driven applications.- Work with frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, and Hugging Face.- Develop prompt engineering strategies and optimize LLM outputs for accuracy and performance.- Build Retrieval-Augmented Generation (RAG) pipelines using embeddings and vector databases.- Integrate AI models with APIs, databases, and enterprise applications.- Perform data preprocessing, feature engineering, model evaluation, and performance optimization.- Collaborate with product managers, software engineers, and data teams to translate business requirements into AI solutions.- Monitor deployed models and troubleshoot issues related to accuracy, latency, scalability, and reliability.- Implement best practices for responsible AI, data privacy, security, and model governance.- Stay updated with emerging AI technologies, frameworks, and industry developments.Required Skills & Experience :- 3+ years of experience in AI/ML engineering, software development, or a related field.- Strong programming skills in Python.- Hands-on experience developing and deploying machine learning or AI-based applications.- Understanding of machine learning algorithms, model training,



evaluation, and optimization.- Experience with generative AI and large language models (LLMs).- Familiarity with LLM APIs and frameworks such as OpenAI, Anthropic, LangChain, or LlamaIndex.- Experience building REST APIs and integrating AI solutions into applications.- Knowledge of data processing, model evaluation, and AI application performance optimization.- Understanding of databases, data pipelines, and software development best practices.- Solid analytical, problem-solving, and communication skills.Good to Have :- Experience building Retrieval-Augmented Generation (RAG) applications.- Familiarity with vector databases such as Pinecone, Weaviate, or FAISS.- Knowledge of AI agents, multi-agent systems, and workflow orchestration.- Experience with cloud platforms such as AWS, Azure, or Google Cloud.- Familiarity with Docker, Kubernetes, and CI/CD pipelines.- Experience with MLOps, model monitoring, and production deployment.- Knowledge of fine-tuning, embeddings, and evaluation techniques for LLMs.Preferred Candidate Profile :- Ability to convert business requirements into practical and scalable AI solutions.- Robust understanding of AI system architecture and integration patterns.- Experience working in Agile development environments.- A continuous-learning mindset with an interest in emerging AI technologies. (ref:hirist.tech)

📌 Artificial Intelligence Engineer - Generative AI/LLM (Pune)
🏢 Digihelic Solutions Private
📍 Pune