Role Description We're looking for a Senior AI Engineer to join our Platform Team and help scale the core data pipeline infrastructure that powers Improvado—the engine moving data from 500+ marketing platforms to client dashboards. You'll own critical parts of our data extraction and pipeline infrastructure, working hands-on with AI to solve real infrastructure challenges. You’ll work with AI in production: - Using LLMs, agentic coding, and modern tooling to accelerate development - Optimize pipelines and ship faster without sacrificing reliability - Direct impact on how our platform scales Responsibilities - Use AI tooling actively: Claude Code, prompt engineering, agentic coding to accelerate development, write tests, optimize complex problems, and ship faster - Develop and maintain core data extraction and pipeline infrastructure serving 500+ integrations - Own the architecture and execution of pipeline modernization initiatives - Optimize product performance and reliability at scale: identify bottlenecks, manage resource constraints, and ensure data flows without disruption - Drive technical decisions, and maintain high code quality Qualifications - 5+ years of backend engineering experience, with proven ownership of production systems - Deep expertise in Python - Hands-on with modern AI tooling: Claude/Opus, Claude Code, prompt engineering, agentic coding environments—not just familiar, but actively using it to ship - Strong understanding of distributed systems, Kubernetes, and workflow orchestration - Solid SQL knowledge (PostgreSQL, ClickHouse) and ability to optimize queries - Comfortable with ambiguity and ownership mentality—thrives in a fast-paced startup - Ability to work in EST timezone Benefits - Remote-first environment - 20 PTO days + U.S. holidays - Optional relocation assistance to Latin America after your trial period - Modern AI tech stack and freedom to experiment - Extremely fun & open startup environment - Professional development reimbursement

Role Description We are looking for a Senior AI Developer & Cloud Architect to design, build, and own the AI-powered compliance scraping engine and cloud infrastructure layer for an internal platform monitoring up to 70,000 credit card offer pages per month. This is a hands-on, sole-builder contractor role that sits at the intersection of cloud architecture, AI engineering, and large-scale web scraping, with a clear mandate: deliver a production-grade system that detects compliance violations across issuer offer pages with high accuracy and controlled token costs. You will do this by: - Architecting the AWS environment from the ground up. - Building a containerized worker fleet that integrates Playwright rendering with Claude-powered contextual analysis. - Defining clean API contracts with the internal team that owns the Laravel control panel. This is not a managed-PaaS or prototype role. You will be accountable for end-to-end delivery — architecture, build, documentation, and knowledge transfer — owning the full scraping and AI pipeline from URL intake through compliance findings, screenshot evidence, and results delivery back to the portal. Responsibilities - Design and configure the production AWS environment (ECS/Fargate, SQS, API Gateway, RDS PostgreSQL, S3, IAM, CloudWatch) using infrastructure as code (Terraform or CDK). - Build a stateless, containerized worker fleet that integrates Playwright-based page rendering, structured rule evaluation, and Claude API analysis. - Implement token optimization strategies across the LLM pipeline — prompt engineering, context pruning, caching, model selection, and batching — with measurable cost outcomes. - Define and document API contracts, job payload schemas, and database write patterns with the internal Laravel portal team to enable parallel development. - Build third-party API ingestion and field-level diff-detection logic that automatically adjusts monitoring rules when product data changes. - Handle modern web rendering challenges at scale: JavaScript-heavy SPAs, interstitials, cookie consent overlays, dynamic content, viewport switching, and full-page screenshot capture. - Evaluate when LLM analysis is the correct tool versus a classifier or rules-based approach, and design the two-stage rule-engine-plus-AI pipeline accordingly. - Build and maintain a unit test suite covering all modules and APIs to ensure uptime and proper functionality. - Document every architecture decision, configuration, API contract, and operational procedure continuously — not as a final-week deliverable. - Deliver a complete runbook and knowledge transfer to the internal team at engagement close. - Operate independently end-to-end while coordinating closely with the internal portal team and reporting directly to the Senior Director, surfacing risks and trade-offs early. Requirements - Production backend Python experience, including async patterns, type hints, packaging, and testing. - Direct production experience designing and configuring AWS ECS/Fargate, SQS, API Gateway, RDS (PostgreSQL), S3, IAM, and CloudWatch, with infrastructure as code (Terraform or CDK). - Real shipped systems calling the Anthropic Claude API in production, with demonstrated experience in prompt design, structured output, error handling, and cost trade-offs. - Demonstrated track record reducing token spend on production LLM workloads, with specific before/after results you can walk through. - Working knowledge of other LLM providers sufficient to recommend cheaper or better alternatives for specific tasks. - Production Playwright experience at scale, including headless Chromium failure modes, network idle detection, dynamic content handling, viewport switching, and screenshot strategy. Selenium or Puppeteer experience does not substitute. - Machine learning fundamentals sufficient to evaluate when LLM analysis is the right tool versus a classifier or rules-based approach, and to reason about evaluation and false-positive rates. - Docker and containerization experience, including image optimization, ECR, and stateless worker design. - Ability to operate fully independently — no engineering team underneath you — while documenting continuously and coordinating cleanly with an internal team. Nice to Have - Experience with API ingestion and field-level diff-detection systems. - Laravel or PHP familiarity, enough to coordinate cleanly on API contracts with the portal team. - SOC 2 Type II compliance experience. - Salesforce API integration experience. - Regulated-industry experience (financial services, healthcare, or insurance). Benefits - The expected hourly range for this position is $80/hr - 100/hr. This hourly range is an estimate, and the actual hourly rate may vary based on the Company’s compensation practices. - The hourly rate may be adjusted based on applicant's geographic location. - This position is eligible to participate in the Company’s standard employee benefits programs, which currently include health care benefits. Company Description QuinStreet is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, national origin, pregnancy status, sex, age, marital status, disability, sexual orientation, gender identity or any other characteristics protected by law. Please see QuinStreet’s Employee Privacy Notice here.

Additional Information All your information will be kept confidential according to EEO guidelines.

• Design, build, and maintain AI agents, integrations, and automations that reduce manual work, eliminate bottlenecks, and improve productivity across every department at Chipply. • Inspect Chipply's internal SaaS platforms (HubSpot, Microsoft 365, Confluence, Slack, and others) to understand what APIs, webhooks, and MCP connectors they expose, and use those surfaces to build the integrations each team needs. • Partner with leadership and department heads to identify and prioritize high-impact opportunities by mapping existing workflows and pinpointing where engineering effort — AI-powered or deterministic — will deliver measurable improvement. • Write production code. Build multi-tool and multi-agent systems that connect Chipply's internal platforms into seamless end-to-end processes. Make sound judgment calls on when AI is the right tool and when a deterministic solution is a better fit. • Build evals and monitoring for AI systems you ship, so output quality is measurable rather than assumed. • Serve as Chipply's internal AI champion by leading education, training, and adoption efforts, and by acting as the go-to engineering resource for AI questions, best practices, and emerging use cases. • Establish and maintain responsible AI governance, including guidelines for data handling, privacy, model and tool selection, output quality monitoring, and ethical use. • Continuously evaluate emerging AI tools, agent frameworks, model providers, and orchestration libraries; pilot promising technologies and recommend adoption decisions based on impact, cost, and fit. • Measure and report on the ROI of the systems you ship, tracking time saved, error reduction, cost impact, and quality improvements. • Develop and maintain documentation for the systems, integrations, and AI workflows you build so institutional knowledge scales with the company. • Serve as a liaison across Engineering, Finance, Sales, Marketing, Customer Support, and Product to align on technology needs and ship workflow improvements end to end. • Monitor security and compliance across the integrations and AI systems you build, collaborating with engineering and leadership to ensure data protection best practices are followed. • Continuously redefine the scope, priorities, and deliverables of the role as Chipply's needs and the broader AI ecosystem evolve.