AI Solutions Architect
New
J
JobgetherSecurity & IT
Mexico, Required overlap with US time zonesContractSenior
Salary not disclosed
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Job Details
- Experience
- 10+ years of experience in software engineering or machine learning architecture, with at least 5 years focused on enterprise AI solutions.
- Required Skills
- AWSMachine LearningSoftware ArchitectureLLMLangChain
Requirements
- 10+ years of experience in software engineering or machine learning architecture.
- At least 5 years focused on enterprise AI solutions.
- Proven experience designing and deploying multi-agent AI platforms for production-scale workloads.
- Strong expertise in conversational AI systems, session management, and context handling.
- Hands-on experience architecting scalable RAG pipelines, retrieval optimization, and ranking strategies.
- Experience working with multiple LLM providers (e.g., OpenAI, Claude/Bedrock, Gemini) and open-source models.
- Knowledge of real-time and batch machine learning pipelines.
- Strong cloud architecture experience (AWS, GCP, or Azure).
- Experience with AI orchestration frameworks such as LangGraph, LangChain, or LlamaIndex.
- Understanding of AI security, governance, compliance, and responsible AI principles.
Responsibilities
- Review existing AI initiatives with engineering teams, identify improvement opportunities, and help establish a unified AI platform strategy.
- Design reference architectures for multi-agent orchestration, intent classification, routing frameworks, and context management across AI workflows.
- Define strategies for managing AI context, including token optimization, conversation memory, summarization approaches, and information flow between agents.
- Architect Retrieval-Augmented Generation (RAG) solutions, including ingestion pipelines, retrieval strategies, reranking approaches, and quality optimization.
- Establish AI governance practices covering prompt management, testing frameworks, monitoring, version control, and rollback processes.
- Define resiliency patterns for LLM-powered applications, including provider failover, cost management, observability, and graceful degradation strategies.
- Establish AI safety standards related to security, privacy protection, responsible AI practices, and hallucination mitigation.
- Collaborate with technical and business stakeholders to create implementation roadmaps and guide execution priorities.
- Produce architectural documentation, technical recommendations, and strategic guidance to support AI platform development.
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