Back to SearchAI Solution Architect
Remote in Argentina, & 4 others
AI Solution Engineering& 9 others
Looking for something else?
Find a vacancy that works for you. Send us your CV to receive a personalized offer.
Find me a job
Choose an option
We're seeking an AI Solution Architect to come aboard our team. This opportunity suits someone who takes satisfaction in walking teams through the hands-on challenges of constructing and verifying AI-powered systems. You'll collaborate closely with technical specialists and business-side stakeholders alike, helping connect cutting-edge AI potential with practical, applied outcomes. For those energized by a mix of experimental work and structured advisory contributions, this role presents a genuine chance to add real value.
Responsibilities
- Offer hands-on direction regarding agent development, covering model and tool choices, deployment tactics, evaluation approaches, and continuous monitoring
- Assess RAG/GraphRAG options, chunking methods, retrieval techniques, re-ranking strategies, and vector-store alternatives together with the architect, moving forward only with the approach agreed upon in the validation plan
- Establish golden datasets, define quality benchmarks, and build regression tests relying on sanctioned, controlled test data free of personal information
- Construct the approved nonproduction agent workflow using Python whenever bandwidth and readiness allow, covering its tools and a single API or system integration point
- Verify success scenarios, error conditions, and permission-related cases, capturing details on quality, cost of usage, known limitations, and outstanding gaps
- Put together a blueprint for workflow deployment and reuse alongside engineering playbooks, addressing semantic/context management, identity handling, permission structures, and autonomy boundaries
- Break down AI-assisted development methods and agent tooling choices in terms accessible to business users, engineering staff, and the AI team
- Create documented examples and facilitate walkthrough sessions, with advisory scope extending to production-grade lifecycle guidance, excluding actual production rollout and day-to-day operations
Requirements
- At least 8 years of applicable professional background
- A minimum of 3 years spent in Senior, Lead, Manager, or Owner-level positions
- Demonstrated history managing engagements involving teams of 5 or more full-time staff
- Direct experience developing AI agents, spanning design, rollout, and refinement
- Familiarity with Amazon Web Services in support of cloud-hosted AI solutions
- Background evaluating and testing GenAI agents to confirm quality, reliability, and consistent performance
- Advanced capability in Python for constructing and validating AI-based workflows
- Working familiarity with REST APIs to facilitate integration across systems and tools
- Hands-on background with Retrieval-Augmented Generation (RAG) to anchor AI outputs in relevant source material
- Professional proficiency in English (C1)
Nice to have
- Background working with AWS Bedrock to construct and launch generative AI solutions
- Knowledge of Amazon Bedrock AgentCore for assisting with agent coordination and management
- Experience applying MuleSoft to support integration across different systems
- Relevant certification, which would be considered a valuable addition to your qualifications