QA Engineer - Load Testing Specialist (2 months contract)

Position Overview

Monolith AI is seeking an experienced QA Engineer to lead load testing efforts for a critical system

release focused on improving concurrency and high request load handling. This fast-paced, short-

term engagement requires someone who can quickly understand complex distributed systems,

design comprehensive load tests, and work collaboratively with a rapidly growing engineering team

to ensure our new environment meets performance requirements.

Primary Responsibilities

1. Design and Implement Automated Load Testing Framework

◦ Develop comprehensive load tests for FastAPI endpoints, Temporal workflows/

activities, and AWS service interactions

◦ Create realistic test scenarios simulating concurrent workflow execution patterns,

including graph-based workflow orchestration

◦ Build automated test suites that measure system behavior under varying concurrency

levels and request loads

1. Performance Analysis and Bottleneck Identification

◦ Monitor and analyze system performance across the entire stack (API layer,

Temporal workers, AWS services)

◦ Identify concurrency limitations in Temporal workflow execution, AWS service

limits (Athena, ECS), and inter-component communication

◦ Document performance characteristics including response times, throughput limits,

and failure modes under load

1. Collaborate on Non-Functional Requirements (NFR) Definition

◦ Work with Customer Success and Product teams to understand business

requirements and translate them into measurable performance criteria

◦ Iterate on acceptable concurrency thresholds, latency targets, and throughput

requirements◦ Validate that proposed NFRs are realistic and achievable given architectural

constraints

1. System Documentation and Knowledge Extraction

◦ Understanding of the existing system through code review, discussions with the

development team, and exploratory testing

◦ Create clear documentation of test methodologies, results, and recommendations for

future testing

1. Recommendation and Optimization Guidance

◦ Provide actionable recommendations for removing identified bottlenecks

◦ Suggest configuration optimizations for Temporal (worker pools, task queues) and

AWS services (Athena concurrency, ECS capacity)

1. Rapid Communication and Status Reporting

◦ Maintain daily/frequent communication with the Tech Lead regarding project

progress, blockers, and findings

◦ Quickly escalate issues that could impact the aggressive timeline

◦ Present findings and recommendations to technical and non-technical stakeholders

1. Cross-Component Integration Testing

◦ Test complex scenarios involving graph execution triggering node workflows across

multiple system boundaries

◦ Validate S3 read/write operations under concurrent load

◦ Ensure inter-component communication (API → Temporal, Temporal Activity →

API triggers) performs reliably at scale

Key Performance Indicators

1. Test Coverage and Execution

◦ Complete automated load test suite covering all critical components within first 3

weeks

◦ Execute baseline and progressive load tests identifying maximum sustainable

concurrency levels

1. Bottleneck Identification and Impact

◦ Identify and document top 5-7 performance bottlenecks with clear impact analysis

◦ Provide actionable remediation recommendations with estimated effort and impact

for each bottleneck

3. NFR Definition and Validation

◦ Collaborate with stakeholders to define measurable NFRs within first 2 weeks

◦ Validate system meets or document gaps against agreed NFR criteria by project end

1. Documentation and Knowledge Transfer

◦ Deliver comprehensive test documentation, results analysis, and system performance

characteristics

◦ Conduct knowledge transfer sessions ensuring team can maintain and extend testing

framework

1. Project Velocity and Communication

◦ Meet weekly milestone targets in this fast-paced 2-month engagement

◦ Maintain proactive communication rhythm (daily standups, weekly detailed reports

to Tech Lead)

Required Qualifications

Experience:

• 4+ years of experience in QA/performance testing roles

• 2+ years of hands-on experience with load testing distributed systems and microservices

architectures

• Proven experience with load testing tools (e.g., k6, JMeter, Locust, Gatling, Artillery)

• Experience testing workflow orchestration systems (Temporal, Airflow, Prefect, or similar)

• Demonstrated ability to test systems integrating with AWS services (particularly Athena,

ECS, S3)

Technical Skills:

• Strong proficiency in Python (required for test automation and working with FastAPI/

Temporal)

• Experience with REST API testing and performance validation

• Understanding of distributed systems concepts: concurrency, queueing, backpressure, rate

limiting

• Familiarity with AWS infrastructure and service limits• Experience with monitoring and observability tools (Prometheus, Grafana, Datadog, or

similar)

• Proficiency with Git and CI/CD pipelines

• Ability to read and understand code in order to design effective tests

Immediate Availability:

• Ability to start in early January 2025 and commit to focused 3-month engagement

• Availability for full-time contract work during project duration

Preferred Qualifications

• Direct experience with http://Temporal.io (workflows, activities, workers)

• Experience with containerized workloads and Docker/ECS

• Prior work in fast-paced startup or scale-up environments

• Experience with infrastructure-as-code (Terraform, CloudFormation)

• Background in Site Reliability Engineering (SRE) or DevOps practices

• Familiarity with data processing pipelines and analytics systems

• Previous contract/consulting experience with rapid knowledge acquisition

• Experience with graph-based workflow systems or DAG execution engines

• Knowledge of AWS service limits and optimization strategies

Essential Soft Skills

Self-Direction and Initiative:

• Ability to operate independently in an ambiguous, fast-moving environment with minimal

documentation

• Proactive problem-solving mindset; doesn't wait for perfect information before taking action

• Comfortable making pragmatic decisions quickly in a time-constrained project

Communication and Collaboration:

• Exceptional communication skills for extracting knowledge through conversations with

existing team members

• Ability to translate technical findings into clear, actionable recommendations for diverse

audiences• Comfortable asking clarifying questions and challenging assumptions respectfully

• Strong written communication for documentation and status updates

Adaptability and Learning Agility:

• Quick learner who can rapidly understand complex, poorly documented systems

• Flexible and comfortable with changing priorities in a 15-person team that's doubling in size

• Thrives in fast-paced environments with aggressive timelines

Pragmatism and Results Orientation:

• Focused on delivering practical, actionable outcomes within tight timeframes

• Understands the balance between thoroughness and speed in a 2-month engagement

• Comfortable with "good enough" when perfect isn't achievable within constraints

Stakeholder Management:

• Skilled at managing expectations with technical leadership about realistic timelines and

trade-offs

• Diplomatic when delivering difficult news about performance limitations or bottlenecks

• Collaborative approach when working with CS and Product on NFR definition

Key Challenges in This Role

1. Rapid Knowledge Acquisition with Limited Documentation

◦ The existing system lacks comprehensive documentation, requiring you to quickly

build understanding through code review, system exploration, and frequent

discussions with the development team

◦ Success requires comfort with ambiguity and strong investigative skills

1. Aggressive Timeline with High Impact

◦ A 3-month timeline to design tests, execute comprehensive load testing, identify

bottlenecks, and deliver actionable recommendations is extremely tight

◦ Must balance thoroughness with pragmatism; prioritize ruthlessly to ensure critical

areas are covered

1. Complex Distributed System with Multiple Integration Points

◦ The system involves multiple layers (FastAPI, Temporal, AWS services) with

complex inter-component communication patterns (graph → node workflows)◦ Must understand the entire stack sufficiently to design realistic, comprehensive load

tests that expose real-world bottlenecks