Artificial Intelligence Engineer

Talenzaa is seeking an Artificial Intelligence Engineer with extensive experience in AI and ML foundations. The role involves developing and deploying LLM-based applications, working with generative AI technologies, and integrating these solutions within enterprise applications.

Responsibilities:

• Strong foundational knowledge in GenAI, Machine Learning (ML modeling), Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and Large Language Models (LLMs)
• Extensive hands-on experience with leading LLMs such as Google Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-source LLMs
• Deep working knowledge and hands-on experience with Retrieval-Augmented Generation (RAG) pipelines, including advanced RAG techniques and their detailed implementation
• Proven ability to build, tune, and deploy LLM-based applications using platforms like Vertex AI, Hugging Face, etc
• Expertise in developing robust prompt engineering strategies, prompt tuning, and creating reusable prompt templates
• Hands-on experience with agentic framework-based use case implementation
• Working knowledge of Guardrails and methodologies for assessing the performance and safety of GenAI features
• Strong programming proficiency in Python is a must, including extensive experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex
• Proficiency in integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration tools
• Hands-on experience with various vector databases (e.g., PG Vector, Pinecone, Mongo Atlas, Neo4j) for efficient data storage and retrieval
• Experience in dealing with large amounts of unstructured data and designing solutions for high-throughput processing
• Hands-on experience deploying GenAI-based models to production environments
• Strong understanding and practical experience with MLOps principles, model evaluation, and establishing robust deployment pipelines
• Strong expertise in CI/CD principles and tools (e.g., Jenkins, GitLab CI, Azure DevOps, ArgoCD) for automated builds, testing, and deployments
• Proven experience with container orchestration platforms like OpenShift or Kubernetes for deploying, managing, and scaling containerized applications in a cloud-native environment
• Strong problem-solving abilities, excellent collaboration skills for working effectively with cross-functional teams, and the capability to work independently on complex, ambiguous problems