Solutions Architect
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Key skills for this role
About the Role
PeoplePilot is looking for a Solutions Architect with strong experience in multi-agent AI architecture, Vertex AI, and GCP AI services. You will design and govern AI solutions, including RAG pipelines, agent memory, and LLM evaluation frameworks.
Key Skills for This Role
Responsibilities
- Design and govern multi agent AI architecture
- Design RAG pipelines using secure coding knowledge packs
- Design agent memory using vector databases or knowledge graphs
- Design secure, explainable AI outputs and governance for model versioning and evaluation
Requirements
- Strong experience designing and governing multi agent AI architecture
- Hands on experience with Vertex AI and GCP AI services
- Strong prompt engineering experience with LLMs such as GPT, Claude, and Gemini
- Experience with LangChain, Semantic Kernel, and AI agent frameworks
- Experience designing RAG pipelines using secure coding knowledge packs
- Strong knowledge of vector databases and embeddings, including Pinecone, FAISS, and Vertex embeddings
- Strong Python experience and experience with ML pipelines
- Experience designing agent memory using vector databases or knowledge graphs
- Experience with LLM evaluation frameworks, including accuracy, false positives, latency, and judge scoring models
- Ability to design secure, explainable AI outputs and governance for model versioning and evaluation
Full Job Posting
Must Have Skills
- Strong experience designing and governing multi agent AI architecture.
- Hands on experience with Vertex AI and GCP AI services.
- Strong prompt engineering experience with LLMs such as GPT, Claude, and Gemini.
- Experience with LangChain, Semantic Kernel, and AI agent frameworks.
- Experience designing RAG pipelines using secure coding knowledge packs.
- Strong knowledge of vector databases and embeddings, including Pinecone, FAISS, and Vertex embeddings.
- Strong Python experience and experience with ML pipelines.
- Experience designing agent memory using vector databases or knowledge graphs.
- Experience with LLM evaluation frameworks, including accuracy, false positives, latency, and judge scoring models.
- Ability to design secure, explainable AI outputs and governance for model versioning and evaluation.
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