AI/AWS Cloud Architect

TEKsystems•San Diego, CA

7d•$80 - $100•Hybrid

About The Position

We’re looking for a hands‑on AWS Architect who’s excited to help enable and scale AI capabilities across a large, complex enterprise environment. This role is ideal for a strong cloud architect who wants to grow into AI/ML and generative AI solutions while staying deeply technical. You’ll work in an environment with hundreds of enterprise applications—from legacy systems to modern low‑code platforms—where AWS is the cloud backbone and AI adoption is rapidly accelerating. While experience building AI agents or working with Amazon Bedrock is a plus, deep AWS expertise, serverless engineering skills, and the curiosity to learn AI frameworks quickly are the real must‑haves. This is a highly impactful role with visibility across teams, where you’ll influence architecture decisions, build working solutions, and help shape the organization’s AI enablement roadmap.

Requirements

Strong hands‑on experience architecting and building AWS‑native solutions.
Deep experience with: AWS Lambda, API Gateway, S3, DynamoDB
IAM and security best practices
Event‑driven and serverless architectures
Designing, building, and consuming APIs
Experience integrating AWS services into enterprise‑scale applications.
Demonstrated ability to learn new technologies quickly, especially AI/ML tooling.
Strong API integration experience.
Familiarity with CI/CD pipelines, DevOps practices, and Git‑based workflows.
Experience with or interest in low‑code platforms (such as OutSystems, Power Apps, ServiceNow).
Ability to guide teams and recommend scalable architectural solutions.
Strong research mindset with curiosity about emerging AI technologies.
Clear, confident communication with both technical and non-technical stakeholders.

Nice To Haves

Experience with any of the following is helpful but not required for strong AWS candidates: Amazon Bedrock models (Anthropic, Titan, Llama, Cohere)
AI agent frameworks, retrieval workflows, and prompt engineering
OpenAI or Anthropic API integration using Lambda
Amazon SageMaker or legacy ML workflows
Experience working in large, enterprise environments.
Exposure to low‑code platform integrations.
Hands‑on development of AI prototypes, pilots, or proofs of concept.

Responsibilities

Design and implement AI‑enabled solutions on AWS, with a growing focus on generative AI and orchestration patterns.
Support the development of AI agents, multi‑agent workflows, and intelligent automation.
Build and evolve knowledge bases, retrieval pipelines, prompts, and guardrails.
Develop serverless AWS components including: AWS Lambda API Gateway S3 DynamoDB Step Functions
Create lightweight integrations and low‑code connectors using serverless services to embed AI into existing applications.
Serve as a hands‑on AWS subject matter expert who grows into an AI solutions advisor.
Mentor development teams (including low‑code teams) on scalable cloud and AI integration patterns.
Rapidly research and evaluate new AI tools, models, and frameworks, applying them pragmatically.
Provide architectural guidance, unblock technical challenges, and propose reusable solution patterns.
Partner with cloud architects, application teams, and product owners to deliver end-to-end solutions.
Evaluate feasibility for AI‑driven enhancements and help scope implementation efforts.
Support integration across data platforms, low‑code tools, and enterprise applications.
Contribute to AI governance, model lifecycle best practices, and cost optimization discussions.
Help define reference architectures and reusable cloud/AI patterns.
Participate in technical interviews and candidate evaluations for cloud and AI engineering roles.