AES - DE - Generative AI Solution Architect

R_344651 Senior Staff Engineer – Advanced Capability Expectations

 

1. Systems & Architecture Leadership

   1. Designs platform-level, cloud-native architectures that scale across multiple teams

   2. Anticipates scaling challenges, failure modes, and long-term evolution

   3. Defines and drives technical strategy, not just implementation

   4. Expected Evidence:

      1. Systems adopted by multiple teams or used at organizational scale

      2. Architecture diagrams with clear design rationale

2. Architectural Decision-Making

   1. Demonstrates structured decision-making across:

      1. Performance vs cost vs reliability vs complexity

      2. Build vs buy vs open source

      3. Synchronous vs asynchronous design

   2. Clearly articulates tradeoffs and alternatives

   3. Expected Evidence:

      1. Documented design decisions

      2. Ability to explain why a solution was chosen over others

3. Execution Speed & Delivery

   1. Able to:

      1. Set up environment quickly

      2. Understand existing systems rapidly

      3. Deliver working proof-of-concepts within 1 day

   2. Maintains high code quality under time constraints

   3. Expected Evidence:

      1. Examples of rapid POC delivery

      2. Demonstrated ability to contribute within first few days of onboarding

4. Platform Engineering & Developer Experience

   1. Builds reusable platforms, frameworks, and developer tools

   2. Improves:

      1. Developer productivity

      2. Deployment pipelines

      3. Onboarding experience

   3. Designs systems with self-service capabilities

   4. Expected Evidence:

      1. Internal tools, SDKs, or frameworks built

      2. Measurable improvements (e.g., reduced build time, faster deployments)

5. Security & Reliability by Design

   1. Applies secure-by-design principles:

      1. Authentication/authorization

      2. Secrets management

      3. Least privilege access

   2. Incorporates:

      1. Observability (logs, metrics, tracing)

      2. Resilience (retries, fault tolerance)

   3. Expected Evidence:

      1. Systems designed with security controls

      2. Experience with AWS IAM, KMS, VPC, or equivalent

6. Advanced Cloud & Distributed Systems Expertise

   1. Strong experience with:

      1. Event-driven architectures

      2. Distributed systems patterns

      3. High-scale systems

   2. Deep AWS knowledge including:

      1. Lambda, ECS/EKS, API Gateway

      2. SQS, SNS, EventBridge

      3. DynamoDB, RDS

   3. Expected Evidence:

      1. Systems handling high throughput or large-scale workloads

      2. Clear understanding of consistency, retries, and failure handling

7. Analytical & Structured Problem Solving

   1. Applies structured reasoning to system design and debugging

   2. Uses:

      1. Data-driven decision making

      2. Testing beyond basics (integration, property-based, etc.)

   3. Expected Evidence:

      1. Examples of debugging complex systems

      2. Thoughtful validation and testing strategies

8. Modern Engineering Practices

   1. Leverages modern tooling and approaches to:

      1. Accelerate development

      2. Improve code quality

   2. Experience with:

      1. AI-assisted development workflows (preferred)

      2. Automation and intelligent tooling

   3. Expected Evidence:

      1. Use of advanced tooling to improve productivity or quality

9. Ownership & Cross-Team Leadership

   1. Operates as a strong individual contributor with leadership impact

   2. Drives alignment across engineering, product, and infrastructure teams

   3. Translates business requirements into scalable technical solutions

   4. Expected Evidence:

      1. Leading initiatives without direct authority

      2. Influencing architecture across teams

10. Demonstrated Impact

    1. Track record of delivering measurable outcomes, such as:

       1. Performance improvements

       2. Reliability gains

       3. Cost reductions

       4. Developer productivity improvements

    2. Expected Evidence:

       1. Quantified results (percentages, metrics, business impact)

 

 

Responsibilities

R_344651 Senior Staff Engineer – Advanced Capability Expectations

 

1. Systems & Architecture Leadership

   1. Designs platform-level, cloud-native architectures that scale across multiple teams

   2. Anticipates scaling challenges, failure modes, and long-term evolution

   3. Defines and drives technical strategy, not just implementation

   4. Expected Evidence:

      1. Systems adopted by multiple teams or used at organizational scale

      2. Architecture diagrams with clear design rationale

2. Architectural Decision-Making

   1. Demonstrates structured decision-making across:

      1. Performance vs cost vs reliability vs complexity

      2. Build vs buy vs open source

      3. Synchronous vs asynchronous design

   2. Clearly articulates tradeoffs and alternatives

   3. Expected Evidence:

      1. Documented design decisions

      2. Ability to explain why a solution was chosen over others

3. Execution Speed & Delivery

   1. Able to:

      1. Set up environment quickly

      2. Understand existing systems rapidly

      3. Deliver working proof-of-concepts within 1 day

   2. Maintains high code quality under time constraints

   3. Expected Evidence:

      1. Examples of rapid POC delivery

      2. Demonstrated ability to contribute within first few days of onboarding

4. Platform Engineering & Developer Experience

   1. Builds reusable platforms, frameworks, and developer tools

   2. Improves:

      1. Developer productivity

      2. Deployment pipelines

      3. Onboarding experience

   3. Designs systems with self-service capabilities

   4. Expected Evidence:

      1. Internal tools, SDKs, or frameworks built

      2. Measurable improvements (e.g., reduced build time, faster deployments)

5. Security & Reliability by Design

   1. Applies secure-by-design principles:

      1. Authentication/authorization

      2. Secrets management

      3. Least privilege access

   2. Incorporates:

      1. Observability (logs, metrics, tracing)

      2. Resilience (retries, fault tolerance)

   3. Expected Evidence:

      1. Systems designed with security controls

      2. Experience with AWS IAM, KMS, VPC, or equivalent

6. Advanced Cloud & Distributed Systems Expertise

   1. Strong experience with:

      1. Event-driven architectures

      2. Distributed systems patterns

      3. High-scale systems

   2. Deep AWS knowledge including:

      1. Lambda, ECS/EKS, API Gateway

      2. SQS, SNS, EventBridge

      3. DynamoDB, RDS

   3. Expected Evidence:

      1. Systems handling high throughput or large-scale workloads

      2. Clear understanding of consistency, retries, and failure handling

7. Analytical & Structured Problem Solving

   1. Applies structured reasoning to system design and debugging

   2. Uses:

      1. Data-driven decision making

      2. Testing beyond basics (integration, property-based, etc.)

   3. Expected Evidence:

      1. Examples of debugging complex systems

      2. Thoughtful validation and testing strategies

8. Modern Engineering Practices

   1. Leverages modern tooling and approaches to:

      1. Accelerate development

      2. Improve code quality

   2. Experience with:

      1. AI-assisted development workflows (preferred)

      2. Automation and intelligent tooling

   3. Expected Evidence:

      1. Use of advanced tooling to improve productivity or quality

9. Ownership & Cross-Team Leadership

   1. Operates as a strong individual contributor with leadership impact

   2. Drives alignment across engineering, product, and infrastructure teams

   3. Translates business requirements into scalable technical solutions

   4. Expected Evidence:

      1. Leading initiatives without direct authority

      2. Influencing architecture across teams

10. Demonstrated Impact

    1. Track record of delivering measurable outcomes, such as:

       1. Performance improvements

       2. Reliability gains

       3. Cost reductions

       4. Developer productivity improvements

    2. Expected Evidence:

       1. Quantified results (percentages, metrics, business impact)

 

 

Qualifications

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