
GenAI Solutions Architect
10 hours ago
Job Overview:
We're seeking an experienced GenAI Solutions Architect to join our team. This contractor role requires a highly skilled professional with deep expertise in Prompt Engineering, Retrieval-Augmented Generation (RAG), and Vector Search Systems.The ideal candidate will have 6–10+ years of engineering experience, with at least 2+ years hands-on experience in GenAI/LLMs/NLP. Strong Python skills and experience in LangChain, Hugging Face, LlamaIndex are required. Additionally, the candidate should have a deep understanding of vector databases and embeddings, as well as proven experience designing and deploying RAG architectures.
Key Responsibilities:
- Design and optimize prompts for LLM workflows ensuring accuracy and relevance.
- Build RAG pipelines using vector DBs (FAISS, Pinecone, Weaviate, Qdrant).
- Integrate LLMs into internal tools, CI/CD, and observability dashboards.
- Fine-tune open-source/commercial LLMs (OpenAI, Claude, Cohere, Mistral) for domain use cases.
- Collaborate with DevOps and platform teams to drive automation with GenAI.
- Ensure data privacy, governance, and ethical AI practices.
Required Skills and Qualifications:
- 6–10+ years in engineering, with 2+ years hands-on in GenAI/LLMs/NLP.
- Strong Python skills with experience in LangChain, Hugging Face, LlamaIndex.
- Deep knowledge of vector databases and embeddings.
- Proven experience designing and deploying RAG architectures.
- Experience integrating LLM APIs (OpenAI, Azure OpenAI, Claude, etc.).
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