Senior Solutions Architect

About the role

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 Solutions 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.

Additional information

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.

Required Skills & Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent experience.
• 7-10+ years of experience in software engineering or cloud architecture with deep AWS ownership.
• Deep expertise in Amazon Bedrock, Bedrock AgentCore, AWS Strands Agents, AgentCore Gateway, and related AWS AI services.
• Strong familiarity with SageMaker (training, deployment, pipelines), deep learning fundamentals, and model fine-tuning strategies.
• Experience architecting RAG, multi-agent, and orchestration systems using AWS-native services.
• Strong knowledge of distributed systems, event-driven architectures, and serverless patterns.
• Proficiency with Infrastructure as Code (AWS CDK, CloudFormation, Terraform).
• Hands-on development capability in Python and AWS SDKs.
• Experience implementing observability and monitoring strategies in AWS environments.
• Proven success leading enterprise-scale AWS transformations.
• Exceptional communication skills for both technical and executive audiences.
• AWS Professional Certifications highly preferred (AWS Solutions Architect - Professional, AWS DevOps Engineer - Professional).

Nice to Have

• AWS Specialty certifications (Machine Learning - Specialty, Security - Specialty).
• Experience with advanced agentic reasoning patterns (ReAct,CoT, Tree-of-Thoughts) implemented on Bedrock.
• Experience building secure multi-account AWS organizations using Control Tower.
• Exposure to data engineering services such as Glue, Redshift, Lake Formation.
• Consulting or professional services background.

Personal Competencies

• Accountability - Owns AWS architectural direction and client outcomes with rigor.
• Adaptability - Rapidly adopts new AWS AI releases and evolving generative AI capabilities.
• Collaboration - Builds trust across engineering and executive stakeholders.
• Execution-Focused - Balances innovation with production-ready AWS delivery.
• Innovation-Minded - Experiments responsibly with emerging AWS AI services.
• Craftsmanship - Designs secure, scalable, and well-documented AWS systems.
• Leadership with Courage - Drives architectural alignment in complex environments.
• Comfort in Ambiguity - Translates unclear AI requirements into AWS-native solution architectures.