Senior AI Solutions Architect, AWS

Provectus

ML Solutions Architect at Provectus designing scalable ML solutions and managing client engagements. Focus on autonomous decision-making and integrating agentic AI technologies for diverse industries.

Posted 6/19/2026full-timeRemote • 🇨🇴 ColombiaSeniorWebsite

Tech Stack

Tools & technologies

AWS

About the role

Key responsibilities & impact

Lead technical discovery sessions with prospective clients to understand business problems and translate them into feasible ML solutions
Design end-to-end ML architectures and author technical proposals, including scope, timeline, cost, and resource estimates
Create and deliver compelling technical presentations and demonstrations to both technical and non-technical audiences
Support General Managers in winning new business through technical leadership
Architect agentic AI solutions leveraging autonomous decision-making, tool orchestration, and LLM-based workflows
Design MCP (Model Context Protocol) integration strategies for client environments
Evaluate and recommend appropriate agent frameworks (LangGraph, Claude Agent SDK, and others) based on client use cases
Develop reference architectures for common agentic patterns including RAG agents, multi-agent systems, and tool-using agents
Build POC demonstrations showcasing agentic capabilities using AI-assisted development tools
Advise clients on build-vs-buy decisions for agentic components and assess AgentOps requirements including monitoring, evaluation, and cost optimization
Serve as the primary technical point of contact throughout the project lifecycle
Manage technical stakeholder expectations and navigate complex organizational dynamics
Build long-term trusted advisor relationships with clients
Collaborate with delivery teams to ensure smooth project handoffs
Provide technical guidance during project execution
Contribute to reusable solution patterns, agentic accelerators, and Provectus AI toolkit documentation
Mentor engineers on client communication and solution design

Requirements

What you’ll need

6–8+ years of demonstrated experience in ML or data science roles
Proven track record in client-facing technical roles, including leading pre-sales or discovery engagements
Portfolio of successfully architected and delivered ML solutions with a history of winning business through technical leadership
Deep understanding of the full ML lifecycle from data ingestion through production deployment
Experience designing scalable, production-grade ML architectures across multiple ML domains (RAG, Computer Vision, Time Series, Recommendation Systems, and others)
Strong experience architecting LLM-based applications, including agentic systems
Proficiency with agent design patterns, state management, and orchestration frameworks (LangGraph, LangChain agents, multi-agent systems)
Hands-on experience with the Claude ecosystem: Claude Code, Claude Agent SDK, and Anthropic's tool ecosystem
Working knowledge of Model Context Protocol (MCP) architecture for designing client integrations
Demonstrated use of AI-assisted development tools (Cursor, GitHub Copilot, Claude Code) for rapid prototyping and POC development
Advanced knowledge of AWS ML and data services including SageMaker, Bedrock, Lambda, and ECS
Deep understanding of Amazon Bedrock agents, knowledge bases, and model hosting options
Experience with serverless architectures (Lambda, API Gateway, Step Functions) for agentic workflows
Knowledge of MLOps, LLMOps, and AgentOps practices including monitoring, evaluation, and cost optimization
Ability to design cost-effective solutions with clear TCO analysis and trade-off assessment
Understanding of data security, privacy, and compliance requirements
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent experience with a demonstrable technical foundation

Benefits

Comp & perks

Remote-first environment with flexible working hours aligned to your local time zone
Competitive salary reflecting client-facing expertise
A budget for your medical insurance
Paid sick leave, vacation, and public holidays
Clear career path toward Practice Leadership or Principal Architect roles
High-visibility role with exposure to diverse global clients and business challenges
Internal training programs covering Leadership, Public Speaking, and technical certifications
Full support for AWS and other professional certifications
Learning budget and conference attendance
Access to the latest AI tools and subscriptions for professional development
Opportunity to work with cutting-edge ML, LLM, and agentic AI technologies
Opportunity to contribute to innovative AI-driven solutions for clients across LATAM, Europe, and North America
Work alongside experienced experts in AI, Data, and Cloud technologies
Equipment and all the tools you need to work productively

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdata scienceML architectureLLM-based applicationsagent design patternsMLOpsLLMOpsAgentOpsdata ingestionproduction deployment

Soft Skills

technical leadershipclient communicationmentoringrelationship buildingstakeholder managementpresentation skillscollaborationproblem-solvingorganizational dynamicstechnical guidance

Certifications

Bachelor's degree in Computer ScienceMaster's degree in Data ScienceMaster's degree in Engineering