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Job Description

We currently have a career opportunity for a QA AI Technical Professional to join our team located in LATAM.

The QA AI Technical Professional is a senior, hands‑on leader focused on defining, building, and scaling AI-enabled QA capabilities across Perficient and key client accounts.

This role combines deep QA and AI/ML knowledge with a strong consulting mindset to shape our AI QA strategy, design technical solutions, support sales and delivery, and drive market differentiation.

The QA AI Technical Professional partners closely with QA Practice Leaders, QA SMEs (Functional, Automation, Performance, Mobile, Data/ETL, Accessibility, Security, etc.), and account teams to research emerging AI technologies, build reusable assets and accelerators, and ensure successful adoption of AI in QA practices. This role is actively engaging with clients’ programs.

Responsibilities

Research, Market Analysis & Benchmarking

- Continuously scan the market for emerging AI/ML technologies, tools, and platforms relevant to QA (e.g., test generation, defect prediction, intelligent automation, code analysis, GenAI for QA).
- Conduct structured competitive analyses, proofs of concept (PoCs), and benchmark evaluations of AI powered QA tools and frameworks.
- Produce clear comparison reports and recommendations (technical, functional, cost, risk) to guide tool selection and strategy.
- Track industry trends, standards, and best practices to keep Perficient at the forefront of AI in QA.

AI QA Technical Solution Design

- Design end‑to‑end AI‑enabled QA solutions and reference architectures that integrate with clients’ existing tools, pipelines, and platforms.
- Collaborate with QA SMEs to embed AI across different testing types: test case generation, test data, regression optimization, nonfunctional testing, risk‑based testing, etc.
- Define technical patterns, APIs, data pipelines, and integration models for using AI services and models (including GenAI, LLMs, and traditional ML) within QA workflows.
- Establish standards and guardrails for responsible, secure, and compliant use of AI in QA.

Sales, Pre‑Sales & Delivery Support

- Support sales and account teams in qualifying and shaping AI QA opportunities with both existing clients and new prospects.
- Lead and/or contribute to solutioning, estimations, and RFP/RFI responses for AI enabled QA engagements.
- Create and deliver compelling, business‑oriented presentations and demos that clearly articulate value, ROI, and differentiation of our AI QA capabilities.

Provide expert guidance during delivery, supporting technical architects, QA leads,



and development teams in implementing AI QA solutions and resolving complex technical issues.

- Understand business challenges, design strategic AI solutions, and pitch it effectively to C‑suite clients.

Use Cases, Assets & Marketing Materials

- Identify high impact AI QA use cases across industries and technologies; prioritize those with strong business value and feasibility.
- Design and build reusable use cases, accelerators, and demo environments that can be leveraged across accounts and pursuits.
- Create technical and business‑friendly collateral (presentations, playbooks, one‑pagers, whitepapers, blogs, videos) to support marketing and sales campaigns.
- Partner with Marketing and QA Practice Leaders to position Perficient as a thought leader in AI‑driven QA Approach.

Partnerships & Ecosystem Management

- Manage and grow relationships with strategic AI and QA tool vendors, cloud providers, and platform partners.
- Evaluate and recommend partnership opportunities to enhance Perficient’s AI QA offerings and go‑to‑market.
- Coordinate joint initiatives with partners (co‑selling, co‑marketing, webinars, pilots, training) and ensure alignment with QA practice strategy.
- Stay current with partner roadmaps and advocate for capabilities that support our clients’ needs.

Talent Strategy & Community Development

- Help define the skills, roles, and competency model required for AI‑enabled QA (e.g., AI QA Engineer, AI Test Architect).
- Work with QA Practice Leaders to shape hiring profiles, training curricula, and certification paths related to AI in QA.
- Mentor QA engineers, leads, and architects on AI concepts, tools, and solution patterns; help upskill teams through workshops and internal enablement sessions.
- Foster an active internal community around AI QA, promoting knowledge sharing, experimentation, and reuse.

Consulting, Collaboration & Stakeholder Management

- Act as a trusted advisor to QA Practice Leaders, engagement leaders, and client stakeholders on the strategic adoption of AI in QA.
- Collaborate closely with QA SMEs across all testing domains to ensure solutions are practical, scalable, and aligned to real delivery needs.
- Lead structured, rational conversations with stakeholders—clarifying goals, constraints, risks,



and expected outcomes of AI initiatives.
- Simplify complex AI and QA concepts for non‑technical audiences, facilitating informed decision‑making.

Qualifications

- Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field; advanced degree or relevant certifications in AI/ML, cloud, or QA (ISTQB, etc.) are a plus.
- 15+ years of experience in QA/Testing, including significant experience in test automation and modern QA practices (Agile, Dev Ops, CI/CD).
- Hands‑on experience with AI/ML and/or GenAI applied to software quality (e.g., test generation, code analysis, defect clustering, NLP‑based testing, LLM‑based assistants).
- Strong understanding of QA tools and ecosystems, plus familiarity with AI platforms and services (cloud AI services, LLMs, ML frameworks).
- Expert at diagnosing business needs, engineering AI strategies, and selling vision to executive leadership.
- Demonstrated consulting mindset: able to structure problems, perform market/technical analysis, synthesize insights, and present clear recommendations.
- Proven ability to design technical solutions and reference architectures that integrate AI into QA pipelines and toolchains.
- Experience supporting pre‑sales and delivery: proposals, estimations, PoCs, demos, and executive presentations.
- Excellent communication and presentation skills, especially with new prospects and senior/executive stakeholders.
- Strong collaboration skills; comfortable working with Practice Leaders, architects, SMEs, sales, marketing, and partners.
- Analytical, data‑driven approach with attention to detail and a focus on measurable outcomes and ROI.
- High level of English written and verbal communication skills.

Benefits

Perficient full‑time employees receive complete and competitive benefits. We offer a collaborative work environment, competitive compensation, generous work‑life opportunities and an outstanding benefits package that includes paid time off plus holidays.

In addition, all colleagues are eligible for a number of rewards and recognition programs including billable bonus opportunities. Encouraging a healthy work/life balance and providing our colleagues great benefits are just part of what makes Perficient a great place to work.

Disclaimer

Disclaimer: The above statements are not intended to be a complete statement of job content, rather to act as a guide to the essential functions performed by the employee assigned to this classification. Management retains the discretion to add or change the duties of the position at any time.

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Postúlate en Kit Empleo: kitempleo.com.co/empleo/1agei6

📌 Latam - QA AI Technical Architect (Colombia)
🏢 Perficient
📍 Colombia