Solutions Architect - AI
Robots and Pencils
| Company | Robots and Pencils |
| Category | Data & Analytics |
| Location | US - Remote |
| Remote | Remote |
| Employment | Not stated |
| Level | Lead |
| Salary | Not stated by the employer |
| Posted | 23 Jun 2026 |
| Last verified | 4 Aug 2026 |
| Source | Employer career page (greenhouse) |
Description
Robots & Pencils is seeking a seasoned AWS AI Solutions Architect to lead the design and delivery of complex, enterprise-grade generative and agentic AI systems built on Amazon Web Services. You will architect scalable, secure, and production-ready AI platforms leveraging Amazon Bedrock, Amazon Bedrock AgentCore, AWS Strands Agents, AWS AgentCore Gateway, Nova Forge, Nova 2 Sonic, and related AWS AI/ML services. As an AWS AI Solutions Architect, you will serve as a strategic technical advisor—translating ambiguity into structured AWS-native architectures, validating designs through hands-on prototyping, and ensuring every solution aligns with the AWS Well-Architected Framework (including ML Lens) while delivering measurable business value.
Key Responsibilities
Client Engagement & AWS Solution s Architecture
Serve as the primary AWS AI architecture partner for strategic clients, driving generative and agentic AI system design from discovery through production.
Lead architecture design using Amazon Bedrock (including foundation models and custom models), Bedrock AgentCore, AWS Strands Agents, and AWS AgentCore Gateway.
Design advanced RAG, Agentic RAG, and multi-agent orchestration architectures leveraging AWS-native services such as Lambda, Step Functions, API Gateway, DynamoDB, Aurora (pgvector), and OpenSearch.
Produce AWS reference architectures, architecture decision records (ADRs), and implementation roadmaps aligned to business objectives.
Validate feasibility through hands-on prototyping in Python using Bedrock SDKs, SageMaker, and serverless services.
Ensure architectures follow AWS security best practices (IAM, KMS, VPC, PrivateLink) and cost optimization principles.
Outcome Ownership & Business Impact
Own architectural integrity from concept through production deployment on AWS.
Align solutions with AWS Well-Architected Framework pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability.
Guide clients through tradeoff decisions across model selection (Bedrock FMs vs custom SageMaker models), latency, cost, governance, and compliance. Accelerate time-to-value through reusable AWS accelerators, Infrastructure as Code (CloudFormation/Terraform/CDK), and CI/CD automation.
Continuously evaluate emerging AWS AI capabilities (Nova Forge, Nova 2 Sonic, Bedrock updates, and new AgentCore capabilities).
Engineering Leadership & Delivery Excellence
Provide architectural oversight to Forward Deployed Engineers and AWS delivery teams.
Establish best practices for MLOps on AWS including model lifecycle management, monitoring, and observability using SageMaker, CloudWatch, CloudTrail, and AWS Config.
Define governance, responsible AI guardrails, Bedrock Guardrails configuration, and security controls for enterprise environments.
Mentor engineers on AWS AI service integration, distributed systems design, and secure multi-account strategies.
Make principled tradeoffs under constraints related to privacy, compliance (SOC2, HIPAA, GDPR), cost, and operational complexity.
Cross-Functional Collaboration
Partner with internal product, engineering, research, and customer success teams to evolve AWS-based AI offerings.
Contribute AWS reference architectures and reusable infrastructure modules to internal accelerators.
Support pre-sales engagements including architecture workshops, AWS migration strategy, and solution scoping.
Collaborate across distributed teams and client stakeholders across North America.
Require
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