Genius Match

Our client is the leader in the Early Childhood Education (ECE) sector, providing the most widely used developmental assessment and curriculum system in the US. 

They are early in shaping how AI changes the way they build and operate software. They have active initiatives in AI tooling cost-management and agentic development workflows, but their direction is still forming and will keep evolving as the field does. 

They are not looking for someone to execute a fixed plan, they are looking for an experienced practitioner who can validate the direction we are setting, bring expertise we do not have in-house, stay ahead of what is emerging, and help us adjust and grow as the landscape shifts. This person is hands-on enough to build and prove things directly, and senior enough that we trust their judgment on where to place bets.

What you will do

• Act as a hands-on technical partner across AI engineering initiatives, currently spanning tooling cost management, model routing and selection, and agentic development workflows.
• Pressure-test the approaches they are considering, tell them where they are wrong or where a better path exists, and back it with evidence rather than opinion.
• Bring outside expertise and patterns from how other organizations are solving these problems, so they are not learning everything the expensive way.
• Track what is emerging across models, tooling, frameworks, and techniques, and translate it into concrete recommendations on what they should adopt, defer, or ignore.
• Build and run proofs of concept to validate ideas quickly, then help them decide what to operationalize.
• Help mature their agentic development workflow so engineering teams can adopt it, including model routing and token efficiency.
• Partner with Infrastructure and Security so that what they build fits their architecture and meets their data privacy obligations.
• Help them build internal capability, so the expertise compounds with their team and does not leave when the engagement ends.

Required background

• 7+ years in software, platform, or ML engineering, with recent, direct experience building and operating LLM-backed systems in production.
• Demonstrated breadth across the current AI engineering stack: models and their tradeoffs, inference cost dynamics, gateways and routing, agentic workflows, and the AI coding tool landscape.
• A track record of forming a point of view on fast-moving technical decisions and being right often enough to be trusted with them.
• Strong hands-on engineering ability. This person builds, benchmarks, and ships, not just advises.
• Comfort operating with ambiguity and early-stage direction; able to bring structure rather than wait for it.

• Cloud and infrastructure fluency (AWS preferred, including Bedrock).

   

Strongly preferred

• Experience helping an organization adopt AI-first engineering practices, not just individual tool use.
• Hands-on model evaluation and routing design, and exposure to AI cost governance.
• Experience in regulated data environments. 
• A habit of staying current through real practice (building, writing, contributing) rather than headlines.

What this role is not

• Not a fixed-scope implementation seat. The work will change as their direction evolves, and they want someone who helps drive that change.
• Not a data science or model training role. The focus is applied AI engineering, integration, and enablement.
• Not a manager. Individual contributor, hands-on, with influence earned through expertise.

Our client is looking for a Chief Agentic Systems Architect to transform a 10+ year legacy codebase into a high‑velocity, agent‑operable architecture. 

This role sits at the intersection of software architecture, AI‑agent orchestration, and engineering governance. You will design system patterns, MCP interfaces, and cognitive context layers that allow LLMs and autonomous agents to safely refactor, test, and ship production code with minimal human intervention.
 

Responsibilities:

• Decompose legacy monoliths into agent‑readable, modular systems with strict boundaries and single responsibility
• Lead incremental modernization using the Strangler Pattern, wrapping legacy logic in modern, contract‑driven interfaces
• Architect and maintain the agent context layer: standardized Skills, Rules, and Commands for AI‑driven engineering workflows
• Build and operate Model Context Protocol (MCP) servers exposing legacy APIs, services, and databases as typed, secure, AI‑consumable tools
• Own contract‑first API design as the primary interface between human intent and autonomous agent execution
• Act as architectural gatekeeper for AI‑generated pull requests, ensuring scalability, security, and long‑term maintainability
• Mandate test‑driven development (TDD) and characterization testing to preserve legacy behavior during refactoring
• Monitor and optimize agentic reasoning loops to balance cost, speed, and architectural integrity

Requirements:

• 15+ years in software architecture, platform engineering, or technical leadership
• Deep hands‑on expertise with TypeScript, .NET, and Node.js
• Proven experience modernizing large, undocumented legacy systems
• Strong background in API design, distributed systems, and modular architectures
• Practical experience with agentic development, MCP, LLM tooling, or AI‑assisted engineering
• Bias toward clean code, deterministic systems, and production‑grade AI 

• Availability to work until 2 pm - 3pm US EST

   

Will be a plus:

• Experience with remote‑first or globally distributed teams
• Background in SaaS transformations, scale‑ups, or PE‑backed environments
• Comfort operating in high‑ambiguity, high‑ownership settings

Why this role matters:

• You are not adding AI features.
• You are designing the architectural substrate that allows AI to safely build software at scale.
• This is a career‑defining role for architects shaping how autonomous systems write, change, and govern production code.

ROLE OVERVIEW 

As our client's Chief Agentic Quality Architect, you will orchestrate the transition from traditional scripted testing to an AI-augmented quality ecosystem.

Your primary goal is to leverage agentic AI tools to generate, execute, and maintain high-fidelity test suites that keep pace with a development environment where AI agents are writing a significant portion of the production code. 

WHAT YOU'LL DO 

1. Assess & Benchmark Quality Coverage 

• Take ownership of a new product or suite of products as a hands-on quality leader. Conduct a comprehensive audit of the existing test estate across all layers — unit, integration, API, UI, sanity, and regression — evaluating depth, coverage, and reliability of each suite. 
• Evaluate the current QA tooling, frameworks, and automation maturity against client's quality benchmarks and coverage expectations. Identify systemic gaps, test debt, and high-risk areas with no automated coverage. 
• Produce a Current State & Gap Coverage Report that maps existing tooling, highlights missing coverage domains, and recommends the adoption tooling needed to close the gaps — the baseline for every roadmap that follows. 

2. Define the Quality Engineering Roadmap 

• Define missing test cases and user journeys. Prioritise end-to-end automation across critical business flows using agentic automation patterns, with a deliberate emphasis on left-heavy coverage — maximising unit and integration depth first, and extending rightward through black-box UI and regression testing. 
• Architect and own the phased quality engineering roadmap, structured as three delivery horizons: 
• Two-Week Plan: Complete the current-state assessment; identify the highest-risk coverage gaps; stand up quick-win automation on the most critical user journeys; evaluate and select the tooling to be adopted. 
• One-Month Plan: Core regression coverage established across primary domains; CI/CD quality gates operational and integrated into the development pipeline; agentic test generation producing its first validated suites. 
• Three-Month Plan: End-to-end agentic automation live and self-maintaining; Client's benchmark coverage achieved; AI guardrails enforced across all automated agent output; quality metrics visible to engineering leadership. 

3. Agentic Test Generation & Automation 

• Prompt-Based Engineering: Utilise AI agents to automatically transform business requirements and manual test cases into executable Playwright or Cypress scripts. 
• Synthetic Test Creation: Implement tools that autonomously generate test data and edge-case scenarios that human testers might overlook. 
• Autonomous Maintenance: Deploy self-healing automation frameworks that use AI to detect UI changes and update test selectors without human intervention. 

4. Guardrails for AI-Generated Code 

• Agent Regression Strategy: Design and own a comprehensive regression suite specifically tuned to catch the non-deterministic “hallucinations” or logic errors common in AI-generated code. 
• Behavioral Locking: Implement characterisation testing patterns to “lock in” the expected behaviour of legacy systems during AI-assisted refactoring. 
• Autonomous Output Validation: Define quality gates to validate the outputs of autonomous agents, ensuring they meet functional, security, and performance boundaries. 

5. Build & Mentor an AI-Skilled QA Team 

• Hire QA engineers with deep, hands-on capability in AI-assisted testing and agentic automation frameworks — not generalists, but specialists who can design, implement, and operate AI-driven quality systems in production. 
• Mentor and upskill the team on agentic workflows, guardrail frameworks, and quality benchmarks. Set the technical bar and hold the team to it through code reviews, pairing, and structured coaching. 
• Instil a quality-first engineering culture where QA is embedded throughout the development lifecycle — not a downstream gate — and every AI-generated change is treated as a quality risk until validated. 

WHAT WE'RE LOOKING FOR 

• 10+ years in QA automation engineering, SDET, or test architecture roles 
• Automation Frameworks: Expert-level proficiency in Playwright, Cypress, or Selenium. 
• AI Tooling: Hands-on experience using LLMs (Claude, GPT-4, etc.) and agentic frameworks to generate code or automate workflows. 
• CI/CD Mastery: Deep understanding of integrating quality gates into AWS-based pipelines or similar environments. 
• Architectural Mindset: Ability to design "Behavioral Snapshots" to safeguard critical business logic during rapid transformations
• Availability to work until 2 pm - 3 pm US EST

NICE TO HAVE 

• Experience in remote-first or globally distributed engineering teams 
• Background in SaaS scale-ups, legacy modernization projects, or PE-backed environments 
• Exposure to performance, load, or security testing tooling 
• Comfort operating in high-ambiguity, high-ownership environments with evolving requirements 

Our client is a leading provider of enterprise software solutions, helping organizations optimize complex business processes through innovative technology. The company is committed to delivering high-quality implementation services, driving customer success, and continuously improving its platform through modern technologies and collaborative delivery practices.

They are looking for an experienced Functional Analyst to join the Delivery Services team. In this role, you will be responsible for supporting software implementations, gathering and documenting business requirements, configuring solutions, conducting client training, and ensuring successful adoption of the platform. This position is ideal for someone who enjoys working directly with customers, solving business challenges, and managing multiple implementation projects in a fast-paced environment.

Working Hours: This role requires working at least until 5 PM EST (U.S. Eastern Time) to ensure daily overlap with the client's team.

Responsibilities

• Lead client-facing discovery sessions, product demonstrations, workshops, training sessions, and implementation activities.
• Gather, analyze, and document business and functional requirements.
• Translate business needs into system configuration and functional specifications.
• Configure the platform according to future-state business processes.
• Troubleshoot system issues, analyze errors, and recommend appropriate solutions.
• Support client testing, validation, and user acceptance activities.
• Manage multiple implementation projects simultaneously while balancing priorities and deadlines.
• Collaborate closely with delivery teams, account management, product, and engineering teams.
• Act as the bridge between business stakeholders and software development teams to ensure functional requirements are clearly communicated.
• Continuously learn new tools, technologies, and delivery practices while adapting to changing project priorities.

Requirements

• Bachelor's degree in Business, Information Technology, or a related field.
• 5+ years of experience working with financial aid operations or financial aid systems.
• Strong business analysis and requirements gathering skills.
• Experience configuring enterprise software solutions.
• Experience with data conversion and integrations with external systems.
• Proven experience participating in enterprise software implementation projects.
• Strong analytical and problem-solving abilities.
• Excellent verbal and written English communication skills.
• Experience troubleshooting complex business applications.
• Strong client-facing communication and presentation skills.
• Ability to prioritize multiple projects in a fast-paced environment.
• Experience with Microsoft Office tools, Jira, Confluence, SharePoint, and Project.
• Comfortable delivering training sessions and working directly with business users.
• Strong sense of ownership, teamwork, and customer focus.

Nice to Have

• Experience with higher education or financial aid software platforms.
• Previous experience as a Functional Analyst or Business Analyst within Professional Services or Delivery teams.
• Experience working in higher education administration.
• Experience collaborating with distributed global teams.
• Exposure to high-growth or rapidly changing environments.
• Ability to thrive in fast-paced and evolving organizations.

What We Offer

• Competitive market salary.
• Fully remote work.
• Opportunity to work on impactful enterprise software solutions.
• Collaborative international team environment.
• Professional growth and continuous learning opportunities.
• Exposure to complex implementation projects and modern delivery practices.
• Flexible work environment with required daily overlap of up to 5 PM EST.

Our client is a rapidly growing enterprise software organization that acquires and scales B2B SaaS products. They are building a shared cloud platform that serves as the engineering foundation for a growing portfolio of enterprise applications. This platform provides standardized infrastructure, deployment, observability, automation, and reliability capabilities across multiple products while enabling future growth without proportionally increasing operational complexity.

The organization is investing in modern platform engineering practices, cloud-native technologies, Infrastructure as Code, AI-assisted engineering, and operational automation to build a scalable, highly reliable engineering ecosystem.

They are looking for an experienced Senior Platform & Site Reliability Engineer to take ownership of the shared platform, establish engineering standards, and design the infrastructure that supports multiple enterprise SaaS products. This is a hands-on technical leadership role where you will influence platform architecture, developer experience, operational reliability, and engineering best practices.

Working Hours: This role requires daily collaboration with a U.S.-based engineering team. Candidates must be available to work until at least 5:00 PM EST (U.S. Eastern Time), with flexibility to work beyond these hours when business needs require.

Responsibilities

Platform Engineering

• Own the architecture and operation of the shared platform, including CI/CD, observability, deployment automation, secrets management, and developer tooling.
• Define, implement, and enforce platform engineering standards across multiple products.
• Build and maintain Infrastructure as Code using Terraform or OpenTofu, ensuring all infrastructure is version-controlled, reviewed, and provisioned through automation.
• Develop self-service platform capabilities that enable engineering teams to deploy independently.

Event Streaming & Data Processing

• Design and maintain event streaming infrastructure supporting real-time processing workloads.
• Build and support batch processing infrastructure alongside live transactional systems.
• Ensure reliability, scalability, performance, and cost efficiency of platform services.

CI/CD & Deployment

• Design, build, and maintain CI/CD pipelines using GitHub Actions.
• Automate recovery for common pipeline failures and improve deployment reliability.
• Implement release management strategies, rollback mechanisms, and deployment patterns such as canary or blue-green deployments where appropriate.

Observability & Site Reliability

• Own and maintain the observability platform using Grafana, Prometheus, Loki, CloudWatch, and related monitoring tools.
• Define Service Level Objectives (SLOs), error budgets, and reliability metrics across multiple products.
• Build intelligent alerting and monitoring solutions that provide actionable diagnostic information.
• Design incident response processes, escalation procedures, and post-incident review practices.
• Implement safe automated remediation for well-understood operational scenarios while ensuring human oversight for complex incidents.

Platform Expansion & Integration

• Assess newly onboarded products for infrastructure maturity, Infrastructure as Code coverage, observability, and security.
• Plan and execute platform integration and modernization initiatives while minimizing operational disruption.
• Support the adoption of standardized platform capabilities across multiple engineering teams.

Engineering Automation

• Leverage AI-assisted engineering tools and automation where appropriate to reduce operational overhead.
• Automate infrastructure provisioning, CI/CD workflows, monitoring, secrets management, and operational tasks while maintaining engineering oversight for high-impact decisions.

Preferred Technology Stack

• AWS
• Terraform / OpenTofu
• GitHub Actions
• Grafana
• Prometheus
• Loki
• AWS CloudWatch
• AWS Secrets Manager or HashiCorp Vault
• Amazon ECS and EKS
• Event streaming technologies
• Cost monitoring and cloud optimization tools

Requirements

• 8–12 years of experience in Platform Engineering, Site Reliability Engineering (SRE), DevOps, or Cloud Infrastructure Engineering.
• Proven experience designing and operating production platform infrastructure across multiple environments or products.
• Strong hands-on experience with Terraform (or OpenTofu) and Infrastructure as Code.
• Extensive experience designing and maintaining CI/CD pipelines using GitHub Actions.
• Experience operating event streaming infrastructure in production environments.
• Strong AWS expertise, including ECS, EKS, IAM, VPC, RDS, CloudWatch, networking, and cloud infrastructure.
• Hands-on experience with Grafana, Prometheus, Loki, and enterprise observability platforms.
• Strong understanding of SRE principles, including SLOs, error budgets, incident response, and operational excellence.
• Experience designing scalable, secure, highly available cloud infrastructure.
• Strong troubleshooting, automation, and problem-solving skills.
• Excellent communication skills with the ability to establish engineering standards across multiple teams.

Nice to Have

• Experience building shared platform engineering capabilities supporting multiple products or business units.
• Experience integrating newly acquired products or modernizing legacy platforms.
• Experience designing developer self-service platforms.
• Familiarity with AI-assisted engineering workflows and infrastructure automation.
• Experience supporting high-volume enterprise SaaS products and distributed systems.
• Strong focus on cloud cost optimization and operational efficiency.

What We Offer

• Competitive market salary.
• Fully remote work.
• Opportunity to build and shape the engineering platform supporting a growing portfolio of enterprise SaaS products.
• Work alongside experienced international engineering teams.
• Exposure to modern cloud technologies, AI-assisted engineering, automation, and large-scale platform initiatives.
• Professional growth through ownership of platform architecture, operational reliability, and engineering standards.
• Daily collaboration with a U.S.-based engineering team, with availability required until at least 3:00 PM EST and flexibility to work longer when needed.

Quality Engineer

Our client is the leader in the Early Childhood Education (ECE) sector, providing the most widely used developmental assessment and curriculum system in the US. They are looking for a talented, innovative and creative Quality Engineer to join the platform team. They believe that great technology experts are also software generalists who are unafraid to jump up and down the stack to solve the problems that come their way. If you thrive in fast-paced environments, and like working on software that supports millions of daily users, then this opportunity is exactly what you’ve been looking for!

About the Role

We are looking for a strong Software Engineer who treats quality as part of engineering, not a downstream testing function. This role is ideal for someone who builds high-quality software and uses automation, testing, and AI-assisted workflows to improve engineering speed, quality, and reliability.

This is an AI-first role focused on modern automation, agentic workflows, and shift-left engineering practices.

As a Quality Engineer, you will:

• Build, test, and deliver production-quality software and automation solutions;
• Build and maintain scalable automated testing frameworks using Playwright across UI and API layers;
• Use AI-assisted development and agentic workflows to accelerate validation, debugging, automation, and delivery;
• Own quality and release readiness through automated testing, risk identification, and continuous validation;
• Partner closely with engineering and product teams to embed quality early in the development lifecycle;
• Participate in planning, analysis, and design of scalable testing and automation solutions
• Investigate, troubleshoot, and remedy issues affecting software quality, reliability, and performance;
• Learn new technologies and keep up with both traditional and emerging best practices;

• Work independently and collaborate with other team members to ensure successful project delivery.

   

Qualifications:

• Strong software engineering and problem-solving skills and experience in QA;
• Hands-on experience with Playwright, JAV and modern automated testing practices;
• Experience using Xray for test management and release validation;
• Strong understanding of APIs, modern web applications, and scalable engineering practices;
• Working familiarity with AI-first and agentic development approaches to accelerate implementation and automate complex user workflows;
• Experience building maintainable automated tests across unit, integration, API, and end-to-end layers;
• Strong testing skills across browsers and devices;
• Background in quality engineering or automation-focused software development;
• Experience with security, performance, and resilience testing;
• Interest in continuously learning and evolving modern AI-assisted engineering and automation practices;
• Strong communication and listening skills; ability to communicate complex technical problems, root cause analysis, and propose solutions;
• Experience using AI developer tools (e.g., Codex), with an AI-forward mindset;
• At least Upper-intermediate level of English (B2 or higher);
• Experience with Agile methodology and software development;
• Commitment to following security, accessibility, and performance best practices;
• Self-starter with strong sense of collaboration, teamwork, and accountability;

• Ability to quickly adapt to new environments.

   

We offer:

• Competitive market salary and fully remote work;
• Convenient and somewhat flexible work hours;
• 28 days of paid time off per year;
• Working on a very socially valuable product, alongside a highly professional, US-based, international team;

• Interesting challenges and the ability to grow and learn.