Artificial Intelligence Engineer
vor 12 Stunden
Key Responsibilities
- Develop and integrate LLM-powered applications (e.g., chatbots, summarization tools, workflow automation).
- Build and maintain RAG pipelines including data ingestion, embeddings, retrieval, and evaluation.
- Apply prompt engineering, model optimization, and implement guardrails for safe enterprise AI usage.
- Design scalable APIs and microservices for AI integration into enterprise platforms.
- Deploy models on AWS, Azure, or GCP using Docker and Kubernetes.
- Collaborate with product, data, and engineering teams to deliver impactful AI solutions.
- Stay updated with latest advancements in AI and ML frameworks (e.g., Hugging Face Transformers, LangChain, LlamaIndex, OpenAI, Anthropic, Meta Llama, Mistral).
Required Skills
- Strong Programming Expertise: Proficiency in Python is essential, with experience in building APIs using frameworks like FastAPI, Flask, or similar. Ability to write clean, efficient, and maintainable code.
- Track record of hands-on AI and GenAI solution development and delivery, with a strong understanding of industry-standard frameworks and libraries.
- LLM Framework Experience: Hands-on knowledge of Large Language Model (LLM) ecosystems such as Hugging Face Transformers, LangChain, and LlamaIndex for developing advanced AI-driven applications.
- Vector Database Familiarity: Understanding and practical experience with vector search technologies like FAISS, Pinecone, Weaviate, or Milvus for implementing semantic search and retrieval.
- RAG Architecture & Embeddings: Solid grasp of Retrieval-Augmented Generation (RAG) workflows, embedding models, and techniques for optimizing retrieval performance in AI pipelines.
- Cloud & Containerization Skills: Experience deploying solutions on AWS, Azure, or GCP, along with containerization tools such as Docker and orchestration platforms like Kubernetes for scalable deployments.
- Problem-Solving & Communication: Strong analytical mindset to troubleshoot complex issues and excellent communication skills to collaborate effectively with cross-functional teams.
Nice to Have
- Experience with CI/CD pipelines and cloud-native architectures.
- Exposure to financial services or regulated environments.
- Familiarity with agentic workflows, multi-step orchestration, and LangGraph.
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