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Look4IT

AWS Solutions Architect (AI Implementations)

Remote — United States (see country and timezone requirements)

Check who can apply and the requirements below before continuing.

Job description

This is a remote position.

A leading global IT consulting firm is growing its cloud and AI delivery capability to meet rapidly expanding client demand. We are looking for an experienced AWS Solutions Architect to join our expanding AI project teams — working across a portfolio of enterprise AI implementation engagements and helping our clients turn ambitious AI strategies into production-grade cloud reality.You will be the technical authority on AWS architecture within cross-functional delivery squads — designing solutions, guiding engineering teams, and acting as a trusted advisor to client stakeholders. The role spans multiple concurrent projects with varying domains, scales, and compliance requirements, so the ability to bring structure and clarity to complex situations is just as important as deep technical knowledge.

WHAT YOU'LL BE DOING:

Designing end-to-end AWS architectures for AI and GenAI implementations across multiple client projects

Leading architecture discovery workshops and Well-Architected Framework reviews with client teams

Selecting and configuring the right AWS AI/ML services for each use case — Bedrock, SageMaker, Comprehend, Textract, and beyond

Defining IaC standards and reviewing infrastructure implementations by engineering teams

Advising on data architecture — ingestion, storage, transformation, and access patterns optimised for AI workloads

Working with client security and compliance teams to ensure architectures meet regulatory and enterprise requirements

Contributing to pre-sales and solutioning — proposals, effort estimates, and client technical presentations where needed

Mentoring cloud engineers on the delivery team and conducting architecture and code reviews

Staying current with the AWS AI/ML service roadmap and advising clients on relevant emerging capabilities

Requirements

Proven AWS architecture experience at senior or lead level (5+ years hands-on, across multiple production environments)

Hands-on experience designing and implementing AI/ML solutions on AWS — Amazon SageMaker, Amazon Bedrock, or equivalent managed AI services

Deep knowledge of AWS core services: compute (EC2, ECS, EKS, Lambda), storage (S3, EFS), databases (RDS, DynamoDB, Aurora), networking (VPC, API Gateway, CloudFront)

Experience with Infrastructure as Code — Terraform, AWS CDK, or CloudFormation — with a production track record, not just familiarity

Understanding of data architecture patterns for AI workloads: data lakes, streaming pipelines, feature stores, vector databases

Security-first design mindset — IAM, VPC design, encryption, compliance with GDPR and common enterprise security frameworks

Ability to work directly with clients: translating business requirements into architectural decisions and communicating them clearly to both technical teams and senior stakeholders

English proficiency at B2 or above (working language across international delivery teams and clients)

NICE TO HAVE:

AWS certification — Solutions Architect Professional, Machine Learning Specialty, or equivalent (valued but not a hard requirement)

Experience with GenAI application architecture: LLM integration, RAG (Retrieval-Augmented Generation), agentic AI frameworks (LangChain, LangGraph) running on AWS infrastructure

MLOps experience — model deployment pipelines, monitoring, drift detection, model versioning (SageMaker Pipelines, MLflow, etc.)

Multi-account AWS architecture: AWS Organizations, Control Tower, landing zones

Cost optimisation expertise — FinOps practices, Reserved Instances, Savings Plans, rightsizing for AI/GPU workloads

Experience in regulated industries: financial services, healthcare, or public sector — with associated compliance requirements

Containerised AI workloads: Docker, Kubernetes (EKS), Helm

Observability and monitoring: CloudWatch, AWS X-Ray, OpenTelemetry

Originally posted on Himalayas

Who can apply

Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.

Ready for your next step?Apply on the official website
Apply on Himalayas ↗

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