Test Engineer - AI/ML,

Principal Software Engineer

Location: Bangalore India

Department: AI Engineering / Quality Assurance

Experience Level: Mid to Senior

We are looking for a highly motivated Senior AI Test / Automation Engineer to design and scale automated validation frameworks for AI/ML models, LLM-based applications, and agentic systems. This role is critical to ensure that AI solutions meet enterprise standards for quality, reliability, safety, and compliance before and after production deployment.

Key Responsibilities

• Build and maintain AI test automation frameworks for pre-qualification and continuous validation of models and agent workflows
• Develop comprehensive test suites, including:
• Unit, integration, and end-to-end (E2E)
• Functional, regression, performance, and safety testing
• Validate AI system behavior, including:
• Non-deterministic LLM outputs
• Hallucinations and edge cases
• Multi-step agent decision-making
• Design and manage evaluation systems:
• Golden datasets
• Benchmarking pipelines (accuracy, latency, reliability)
• Automate testing within CI/CD pipelines for model updates, prompt changes, and tool integrations
• Implement observability and telemetry to enable traceability, monitoring, and audit readiness
• Collaborate cross-functionally with ML, MLOps, Product, and Security teams to define quality gates and release criteria
• Track and report quality KPIs, including test coverage, defect leakage, and system reliability
• Drive root-cause analysis and continuous improvement across the AI testing lifecycle

Required Skills

Core Engineering

• Strong programming skills in Python; familiarity with Bash, TypeScript, or Go
• Experience with test automation frameworks such as PyTest, Playwright, Selenium, or Cypress
• Proficiency in CI/CD tools (GitHub Actions, Jenkins, GitLab CI)
• Experience with cloud platforms (AWS, Azure, GCP) and containers (Docker, Kubernetes)

AI / ML & Agentic Systems

• Hands-on experience with LLM ecosystems (OpenAI, Anthropic, Bedrock)
• Familiarity with:
• RAG architectures and vector databases (Pinecone, Weaviate)
• Agent frameworks (LangChain, LlamaIndex, AutoGen)

AI Testing Techniques

• Experience with non-deterministic testing approaches (statistical assertions, tolerance thresholds)
• Knowledge of evaluation methods:
• LLM-as-a-judge
• BLEU, ROUGE, semantic similarity scoring
• Experience with prompt and agent regression testing
• Understanding of AI safety testing, including adversarial testing, bias/fairness validation, and jailbreak detection

Tooling (Preferred)

• AI testing & observability tools: LangSmith, TruLens, Arize, Weights & Biases
• Evaluation tools: DeepEval, Ragas, PromptFoo, Giskard
• Monitoring: Prometheus, Grafana, OpenTelemetry

Soft Skills

• Strong analytical and problem-solving skills
• Excellent communication and cross-functional collaboration
• Data-driven mindset with focus on quality KPIs
• Detail-oriented with a strong bias toward automation and scalability

Experience Requirements

• 7+ years in QA, SDET, or test automation engineering
• Proven experience building and scaling automation frameworks
• Hands-on experience with AI/ML systems or LLM-based applications
• Experience testing RAG pipelines or agentic workflows
• Owned end-to-end AI test strategy and architecture
• Defined quality metrics and release gates
• Delivered scalable validation pipelines for production AI systems
• Supported audit and compliance readiness

Preferred

• Experience in enterprise or regulated environments (SOC2, ISO 27001, etc.)
• Exposure to:
• Shift-left testing practices
• Production observability and monitoring
• Chaos or resilience testing

Senior-Level Differentiators

Education

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field

Nice-to-have:

• ISTQB certification
• Cloud/ML certifications (AWS, Azure, GCP)
• AI testing certifications

What Success Looks Like

• AI systems that are accurate, reliable, and safe
• Fully automated test pipelines integrated into CI/CD
• Measurable improvements in defect leakage and model quality
• Strong observability and auditability across AI systems
• Scalable validation frameworks supporting rapid AI innovation

About the team

SecurITe’s mission is to build an Agentic‑AI driven security platform that protects critical infrastructure from modern cyber threats. Our focus is on delivering highly performant, resilient, and intelligent network security systems that help defenders stay ahead of adversaries.

About the Role

We’re looking for a seasoned Senior Quality Engineer to provide technical leadership and architectural oversight for our next‑generation cybersecurity AI platform. In this high-impact role, you will define the technical strategy for quality assurance, ensuring our agentic AI transforms cyber defense with unparalleled reliability.

You will be responsible for the end-to-end quality lifecycle, from architectural reviews to the deployment of scalable automation frameworks. Beyond technical execution, you will serve as a mentor to junior team members, fostering a culture of technical excellence and driving the strategy that ensures our solutions meet the rigorous demands of critical infrastructure protection.

What You’ll Do

●    Defining and driving comprehensive QA strategies and roadmaps for the cybersecurity platform.

●    Designing, developing, and executing test plans, test cases, and automated scripts to ensure software quality.

●    Performing functional, regression, performance, scalability and security testing to identify bugs or defects.

●    Collaborating with developers, product managers, and other stakeholders to understand product requirements and testing needs.

●    Identifying, documenting, and tracking software defects, ensuring clear communication of issues and their resolutions.

●    Leading deep-dive root-cause analysis for critical system defects and security vulnerabilities.

●    Conducting thorough reviews of product specifications and software design to identify potential areas of concern before testing.

●    Architecting and designing complex, scalable test automation frameworks to optimize CI/CD velocity.

●    Ensuring the software meets customer and business requirements by validating the functionality and performance.

●    Assisting in continuously improving QA processes, tools, and best practices to enhance software testing efficiency and effectiveness.

●    Supporting user acceptance testing (UAT) and assisting clients with product validation.

●    Mentoring junior and mid-level engineers, providing technical guidance and conducting architectural reviews.

Required Experience

●    A Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field.

●    8-10 years of proven experience in quality engineering, specifically within network cybersecurity, Identity Providers, or AI-integrated platforms.

●    Expertise in manual and automated testing.

●    Deep domain expertise in complex system validation and advanced automation practices at scale.

●    Proficiency in programming languages like Python to build and run automated test scripts.

●    "Strong knowledge of software testing methodologies, performance testing tools (e.g., JMeter, k6), and security traffic generation/simulation tools (e.g., Ixia BreakingPoint, Scapy, or Snort/Suricata traffic generators)."

●    Understanding of continuous integration/continuous deployment (CI/CD) pipelines and version control systems like Git.

●    Strong communication skills for documenting test results and interacting with cross-functional teams.

●    Excellent analytical skills, attention to detail, and problem-solving ability.

●    Ability to work independently as well as collaboratively in a team environment.

●    A curious mindset with a willingness to quickly learn new technologies and testing tools.

Required Skills & Qualifications

●    Familiarity with cloud-based testing environments (GCP, AWS, Azure).

●    Experience with cybersecurity products or cloud services or IDP or Web UI

The Mindset

●    Problem Solver: You thrive on complex, ambiguous challenges and engineer elegant solutions.

●    Ownership‑Driven: You take initiative, move fast, and deliver outcomes without hand‑holding.

●    Continuous Learner: You stay ahead of the curve in AI, ML, and emerging technologies.

●    Startup DNA: You excel in fast‑moving environments where priorities evolve and impact is immediate.

What you'll own

The quality charter. Define and evolve the testing strategy — web application, dashboards, APIs, webhooks, and customer integrations. Establish release criteria, coverage expectations, and quality gates that engineers actually respect because they're fast and they catch real bugs. Automation at scale. Build and maintain end-to-end and API automation suites that run on every PR and give a trustworthy signal. Own the flake rate. Design for parallel execution, deterministic test data, and fast feedback — a suite nobody trusts is worse than no suite. Performance and reliability. Design and run load, stress, and soak tests against APIs and the platform. Profile results, isolate bottlenecks with the engineers who own the service, and set up the monitoring that tells us about degradation before a customer does. Leverage through tooling, including AI. Use whatever gets coverage up and cycle time down: LLM-assisted test case generation from specs, AI-assisted authoring and maintenance of automation, synthetic test data generation, log and failure triage. We expect you to be opinionated about where these tools genuinely help and where they produce impressive-looking noise. Raising the bar. Partner with product and engineering from spec through release so quality risk is surfaced during design, not after code freeze. Mentor the QA team and build the practices — bug triage discipline, root cause analysis, prevention over detection — that outlast any single release.

What we're looking for

Must have

3–6 years in QA roles, with meaningful ownership of automation frameworks rather than only executing existing suites.

Strong test automation skills with a modern framework — Playwright, Cypress, or Selenium — and solid coding ability in Python, JavaScript/TypeScript, or Java. You should be comfortable reading application code, not just testing around it.

API testing experience: REST, auth, webhooks and asynchronous event flows, contract testing, and tooling such as Postman, REST Assured, or Pact.

Hands-on CI/CD integration — GitHub Actions, GitLab CI, Jenkins, or equivalent — including making suites fast and reliable enough to gate merges.

Working knowledge of SQL for validating data correctness, and comfort with logs, traces, and observability tooling for debugging.

Rigorous, systematic thinking about edge cases and failure modes, and the communication skills to make quality risk legible to product and leadership.

Nice to have

Experience testing AI, ML, or LLM-based products, and comfort with the reality that outputs are probabilistic rather than deterministic. Familiarity with Docker, Kubernetes, or cloud infrastructure for standing up test environments.

Performance and load testing with k6, JMeter, Gatling, or Locust, plus the analytical ability to turn results into a specific, actionable bottleneck. Exposure to enterprise SaaS with real integration surface area, or to security and compliance testing expectations of enterprise buyers. - Experience as the first or most senior quality voice on a team.

What we offer

Competitive compensation with equity. Direct ownership of a charter that materially affects how enterprise customers experience our product.

Proximity to frontier AI systems in production, and the freedom to use modern tooling to do your job well.

A fast-moving team where the distance between an idea and a shipped change is short.

Title                                 : Senior Data & AI Quality Engineer (Ingestion · Evaluation · Testing)

Experience                    : 5+ years

Work type                      : Chennai - Work from Office/ Other Locations - Remote

Employment Type      : Full Time

Notice Period               : Immediate

Work Day                       :Mon to Fri

Key Responsibilities:

• Ingestion pipelines: Confluence, SharePoint/Microsoft 365 (Graph), and repository connectors — parsing, chunking, metadata, incremental sync, data-quality controls
• Synthetic and non-production data design: corpora shaped to banking IT content (runbooks, incidents, KB articles, change records) with realistic permission structures — the foundation of the cloud-first build
• The evaluation harness as a product: golden question sets, retrieval precision/faithfulness/citation-accuracy scoring, the zero-leakage permission suite, the zero-unauthorized-actions agent suite; CI-integrated regression gates
• Performance and load testing with the platform engineer: concurrency profiles, soak tests, degraded-mode behavior
• UAT orchestration and defect triage across both use cases; acceptance evidence packs per milestone
• Measurement reporting foundations: the before/after value metrics (time saved per incident, per search) the client's executives receive monthly

Technical Skills:

• 5+ years across data engineering and quality engineering with production Python; you have built pipelines AND the tests that police them
• LLM evaluation experience: has designed or operated retrieval/generation quality measurement with numeric thresholds (RAGAS-class metrics, custom harnesses, or equivalent) — not just eyeballed outputs
• Document-processing depth: parsing real enterprise content (tables, permissions, versions, mess), chunking trade-offs, metadata design

• Test-suite craftsmanship: negative and adversarial test design — the leakage suite is a security artifact, and you think like an attacker when writing it
• Load/performance testing experience (Locust, k6, or equivalent) and defect-triage discipline

Strongly Preferred :

Synthetic-data generation for regulated domains; Microsoft Graph and Confluence APIs; Milvus/pgvector; Splunk data onboarding; UAT facilitation with business users; banking data-handling standards

About Ampera: 

Ampera Technologies, a purpose driven Digital IT Services with primary focus on supporting our client with their Data, AI / ML, Accessibility and other Digital IT needs. We also ensure that equal opportunities are provided to Persons with Disabilities Talent. Ampera Technologies has its Global Headquarters in Chicago, USA and its Global Delivery Center is based out of Chennai, India. We are actively expanding our Tech Delivery team in Chennai and across India. We offer exciting benefits for our teams, such as 1) Hybrid and Remote work options available, 2) Opportunity to work directly with our Global Enterprise Clients, 3) Opportunity to learn and implement evolving Technologies, 4) Comprehensive healthcare, and 5) Conducive environment for Persons with Disability Talent meeting Physical and Digital Accessibility standards. 

Software Test Engineer

Location: Bengaluru, India (Hybrid)

Employment Type: Full-time

Experience: 2-5 years

Role Overview

The purpose of the Software Testing Engineer is to validate components of Company's multi-technology energy platform including: EV chargers, energy storage, and embedded energy management technologies. You will develop and automate test cases from requirements, and participate in the development cycle of Company's advanced energy management software platform. You will help drive quality within the company ecosystem by participating in all aspects of black-box API testing for the many EV chargers that company utilizes. You will work with both hardware and software test setups to help company deliver a quality product.

What you’ll do:

• Develop validation and test plans for energy management algorithms in embedded devices
• Develop validation and test plans for OCPP communication protocol
• Install and Maintain AC & DC EVSE Hardware with a focus on safety above all.
• Develop python automation in a Linux environment
• Develop functional, stress and system level test suite and test infrastructure in manual and automated ways
• Develop test capabilities like fault injection, customer scenario simulation, end-to-end functional and performance testing
• Ability to architect and develop strategies to test the system at all levels of the application stack
• Build, manage and execute manual/automated test suites to exercise our world-class software to verify the growing feature sets and customer requirements
• Automate tasks through creation and maintenance of scripts and tools
• Track defects and drive vendors to closure
• Participate in all aspects of the product development process with emphasis on end-to-end system validation
• Lead efforts to obtain and maintain open standard certifications (OCPP, ISO15118, CCS, etc.)
• Maintain internal testing and validation equipment.

What We’re Looking For:

Basic Qualifications

• Bachelor’s degree in computer science or electrical engineering
• 2+ years’ experience working with Python, Scripting, Linux and Networking in a product development environment
• Hands-on experience with Playwright, Selenium, Jupyter, Pandas and other automation tools
• Hands-on experience Websockets, and REST API testing
• Hands-on experience with EVs, and EV chargers
• Hands-on experience with CCS, Chademo, and ISO15118
• Hands-on experience with Battery storage systems
• Experience in AI/ML or Generative AI (GenAI) application testing and validation.
• Hands-on experience with Python libraries such as NumPy and Pandas for test data preparation, analysis, and validation.
• Certified electrician is a plus
• Experience in power systems, grid management, and inverters
• Fast pace learner and self-starter
• Experience with energy storage, EV and electrical distribution preferred
• Knowledge of software requirements, architecture and documentation
• Knowledge of code maintenance, coding standards, and version control
• Work in an Agile (SCRUM) engineering environment
• Excellent verbal and written communication skills, interpersonal skills, collaborative skills, and cross-functional interface skills
• Effective communication of project results in written reports and presentations
• Ability to solve problems by identifying root causes, analyzing possible solutions, and taking appropriate action
• Committed to security practices in policy and delivery
• Show vigilance in reporting of information, security vulnerabilities whether personal devices, corporate assets, services offered to customers, or office environment
• Willing to participate in additional security and privacy trainings
• Willing to be a model citizen/mentor in security practices for Shell Recharge Solutions
• A sense of humor!

What We Offer: 

• A work environment that allows you to work with and learn from some of the best and brightest in this emerging industry 
• The ability to make a difference in a world that needs our technology to help reduce carbon emissions and enable a more sustainable energy future through the use of electric vehicle charging software, services and infrastructure 
• The freedom to learn, suggest, and implement innovative new ideas applied to our systems, processes, programs and technologies 
• Daily ownership of your role in a challenging, high-growth environment.    
• A casual work environment and culture that support work life ‘fit’, enabling you to fit life into your work and work into your life, i.e. flexible scheduling, virtualization options, and a generous holiday package 
• Competitive pay and benefits programs designed to enable you to thrive inside and outside of work
• Participation in Company’ performance and rewards bonus program 
• Best in class medical benefits for employees 
• Innovative Paid Time Off Program  

We are seeking a forward-thinking Mid-Level QA Automation Engineer specializing in RPA, financial systems validation, and AI engineering. You will build and scale end-to-end automation workflows using UiPath for our financial services platform. Additionally, you will pioneer our testing evolution by leveraging prompt engineering, creating custom AI agents, and implementing Model Context Protocol (MCP) servers to bridge AI models with our testing infrastructure.

Key Responsibilities and Duties

   RPA Automation:

·    Design, develop, and maintain robust automated testing workflows using UiPath Studio.

 AI Agent Engineering:

·   Architect, build, and orchestrate custom AI agents to autonomously generate,execute, and self-heal test scripts.

Prompt Engineering:

·   Design, optimize, and manage advanced prompt templates to drive deterministic,high-quality code and test case generation from LLMs.

 MCP Integration:

·    Implement and configure Model Context Protocol (MCP) ecosystems to securely connect AI agents with local data, development tools, and testing environments. 

 Financial System Testing:

·   Validate end-to-end trade life cycles, market data processing, and capital market clearing workflows. 

Regression Orchestration

·   Manage continuous regression schedules via UiPath Orchestrator to ensure financial system stability. 

Mandatory skills

Project Mandatory Skills

Project Desired Skills

UiPath Studio and Orchestrator (UI/API automation activities)

Selenium or Playwright for web-based application testing

Building, deploying, and scripting autonomous AI agents for complex engineering workflows

Calypso treasury and capital markets platform

Prompt engineering — context injection, few-shot prompting, and guiding LLMs to exact test requirements

FitNesse for acceptance testing and collaborative documentation

Model Context Protocol (MCP) — using or developing MCP servers/clients to connect AI tools to external data sources and developer environments

TypeScript, Python, or Java to support agent tool calling and framework extensions

 Qualifications

• 3+ years of professional software QA automation or RPA development experience.
•  Strong understanding of capital markets, trading lifecycles, treasury workflows, or core banking architectures.
• Strong communication and collaboration skills to work across engineering, QA, and business teams.

Senior QA Analyst (Agentic AI)

Location - Chennai

Experience - 5-8 yrs

Job Summary -

Defines, develops, maintains, and executes test scripts for IT projects and/or maintenance items in

an Agile environment utilizing Atlassian JIRA and Zephyr for sprint backlog and test management.

Strives to ensure that user stories and/or system requirements are satisfied for internal and external application users. Ensures project/sprint testing is complete, and testing risks are identified before

implementation. Manages defects from identification to closure through the Software Development Life Cycle. Leverages agentic AI tools and AI-assisted testing platforms to accelerate test design, script

generation, and defect triage, while applying sound professional judgment to validate AI-generated outputs and safeguard overall test quality.

Job Responsibilities -

• Integrated Scrum team member responsible for upholding and ensuring quality assurance standards; contributes and participates in all Scrum activities and ceremonies.

• Defines, develops, and maintains test scripts, leveraging agentic AI tools (e.g., AI-based test-generation and self-healing automation agents) to accelerate script creation and upkeep. Reviews test scripts—including those authored or modified by AI agents—and provides

feedback to less experienced team members.

• Independently executes test plans and test scripts based on planned project schedules and in accordance with QA methodology.

• Proactively escalates issues to the Product Owner/Tech Lead and alerts the project/Scrum team on potential impact to the test schedule.

• Records and tracks defects uncovered during the execution of test scripts, including those surfaced by autonomous AI testing agents. Drives defects toward resolution; proposes and designs retest cases, scripts, and data, using agentic AI to accelerate root-cause analysis where appropriate. Contributes to defect management: defect status, root cause, and daily triage meetings.

• Provides timely and accurate defect status information and appropriate metrics to facilitate QA reporting. Reports individual status: dashboard information, open issues, and risk analysis.

• Participates in validation of release candidate/production deployments and production support testing as needed.

• Provides consistent and uninterrupted testing services to the organization and minimizes risk of system downtime.

• Reviews requirements/user stories and specifications and provides input during requirements and specification walkthroughs.

• Develops and executes SQL queries.

• Configures, directs, and supervises agentic AI testing tools within the QA workflow, including AI agents that generate, execute, and self-heal test scripts. Validates agent-produced results for accuracy and completeness and escalates cases where AI output requires deeper human judgment or intervention.

• Applies effective prompt engineering and critically reviews AI-generated test artifacts (test cases, scripts, data, and defect summaries) for correctness, coverage, and compliance with QA

standards, serving as the human-in-the-loop checkpoint for AI-driven testing activities.

• Uses Claude Code to author, execute, and validate Playwright automation test scripts for UI and API test coverage, reviewing and refining AI-generated automation code to ensure it meets QA

coding standards and reliably validates application behavior.

• Contributes to the development of test plans, the project testing approach, and related documents. Understands and contributes to the process of test estimates and project schedules.

• Participates in test planning, test case design, and test script walkthroughs with QA Leads. Understands testing to be accomplished and suggests changes for efficiencies within or between

projects. Actively participates and contributes to the QA design.

• Adheres to established standards and methodologies, including responsible use and governance of agentic AI testing tools. Utilizes tools and methodologies, including agentic AI and automation platforms, to improve individual effectiveness and increase efficiencies in the QA

process.

• Develops and sustains appropriate relationships and communication with peers and other project team members.

Requirements -

• Bachelor's degree or an equivalent combination of education and work experience.

• Minimum of 5–8 years' experience in Quality Assurance.

• 1+ years' experience leading test projects. Training in project management or equivalent knowledge.

• Experience with, or strong aptitude for, agentic AI and AI-assisted testing tools (e.g., AI-based test generation, self-healing automation, autonomous QA agents) is highly desirable.

Skills -

• Strong leadership capabilities, good judgment, and the ability to work effectively with a diverse workforce.

• Excellent verbal and written communication skills.

• Strong analytical, problem-solving, and planning ability. Detail-oriented and Observant.

• Ability to multitask to accomplish workload efficiently. Excellent time management.

• Good work ethic and general business acumen.

• Proficient in the Microsoft Office suite.

• Working knowledge of agentic AI and AI-assisted testing tools; ability to apply prompt engineering, critically evaluate AI-generated test artifacts, and maintain human oversight and accountability over AI-driven testing outputs.

• Hands-on experience with the Playwright test automation framework and with Claude Code or similar agentic coding tools for generating, executing, and validating automation scripts.

• Experience with the system development lifecycle. Extensive knowledge of test engineering methodologies.

• Working knowledge of testing concepts, verification and validation techniques, defect management, quantitative methods, risk management, and measurement programs.

• Understanding of relational database principles, client/server infrastructure, and n-tier architecture concepts.

• Working knowledge of defect tracking, quality principles, and testing tools.

• Knowledge of MS SQL Server, AWS Postgres, Web, Mobile, Accessibility, and Middle tier testing.

Professional Competencies -

• Ethical decision making: acts in the best interest of the organization, demonstrates integrity in all situations, and holds self and others to the organization's values.

• Focus on business results: understands the financial implications of business decisions, sets ambitious goals, and prioritizes sustained business performance.

• Honoring commitments: meets or exceeds performance expectations and inspires trust by delivering on promises.

• Embracing change: participates actively in the change process, shows resiliency and commitment during times of change, revises priorities and adapts project plans or work tasks as

needed, and takes initiative to improve own capabilities as the business changes.

• Service delivery: delivers service in compliance with contracted agreements, meets or exceeds established performance standards, and uses available tools and systems to deliver timely, accurate work.

About the role

We need a senior QA professional to assess our current QA practices, set up the right processes, and guide junior team members on execution. You will then scale the practice with Playwright automation.

Responsibilities

Assess existing QA processes, tools and coverage; identify gaps and drive an improvement roadmap.

Define test strategy, QA processes and quality metrics (coverage, defect leakage, release sign-off).

Guide and mentor junior QA engineers on test design, execution and automation.

Build a scalable Playwright (TypeScript) framework for UI and API tests.

Integrate automation into CI/CD with quality gates and clear reporting.

Drive adoption of AI in testing: agentic AI for test generation, self-healing scripts and failure triage, using Playwright MCP and similar tools.

Define QA approaches for AI-powered features, including LLM output evaluation and agent workflow testing.

Partner with dev and product teams to make quality a shared responsibility.

Must have

8–10 years in QA, 4+ years in test automation.

2+ years hands-on Playwright with TypeScript/JavaScript.

Proven experience assessing and setting up a QA practice from scratch.

Strong API testing, CI/CD (GitHub Actions, Jenkins or similar) and Git skills.

Experience leading and coaching junior QA engineers.

Hands-on use of AI coding assistants and agentic AI tools (e.g. Playwright MCP, Claude, GitHub Copilot) in QA workflows.

Good to have

Selenium/Cypress to Playwright migration experience.

Performance, accessibility or visual testing exposure.

ISTQB or equivalent certification.

Experience building or testing MCP servers, AI agents or LLM-based applications (evals, prompt and guardrail testing).

Senior QA Engineer

Make quality part of the engineering system.

AbleCredit builds software for complex enterprise workflows where AI, APIs, business rules, human decisions, and real-world operations have to work together reliably. We care about building products that work in production - not just in demos. We're looking for a senior quality engineer who can move quality upstream: from release-time testing to better automation, contracts, observability, and engineering practices.

What You'll Own?

• Own quality strategy across web, mobile, backend APIs, integrations, and end-to-end workflows.

• Design and maintain automated regression suites for critical customer journeys.

• Build API, integration, contract, and workflow tests that catch failures before production.

• Partner with engineering and product teams during design - not only after development is complete.

• Define release readiness, risk-based testing, and production validation practices.

• Investigate escaped defects, identify systemic causes, and drive preventive improvements.

• Improve test data, environments, tooling, and CI integration so teams can ship confidently.

What We're Looking For?

• 5+ years in software quality engineering or test automation.

• Strong API and backend testing experience, including asynchronous and integration-heavy systems.

• Experience testing mobile and web applications and understanding client/ server failure modes.

• Ability to write automation in JavaScript/ TypeScript, Python, Java, or a similar language.

• Strong debugging skills across logs, network requests, databases, and distributed services.

• Experience with CI/CD and integrating automated tests into release pipelines.

• A product mindset: prioritize risk and customer impact rather than maximizing test-case counts.

Nice to Have

• Performance, load, security, or reliability testing.

• Experience with Playwright, Cypress, Appium, Postman/ Newman, k6, or similar tooling.

• Experience with event-driven systems, queues, webhooks, and long running workflows.

• Experience testing AI-assisted or non-deterministic product behavior.

How We Think About Quality?

Quality is an engineering responsibility. Automation should create confidence, not dashboards. A production escape should improve the system that allowed it to happen. The goal is simple: ship quickly without making customers our test environment.

About Us

Invorto is our Voice AI product, bringing intelligent voice agents to real-world customer and operational use cases. Our voice pipeline is built in Python, running an STT → LLM → TTS architecture on top of the Pipecat framework.

This is a chance to work on hard problems in voice AI — latency, accuracy, naturalness, and reliability — building zero-to-one, owning your area end-to-end, and shipping to production at scale.

Note: This is a customer-facing role, and strong communication skills are essential.

About the Role

We're looking for a Voice AI Research Engineer to join the Invorto team and help build and continuously improve the voice AI systems that power our intelligent voice agents. This role is focused on the specialized craft of voice AI — designing evaluation and automation frameworks that ensure our STT, LLM, and TTS pipeline performs reliably in real-world, production conditions.

What You'll Do

• Design and build automated testing and quality frameworks for our STT → LLM → TTS voice pipeline, built on Pipecat
• Evaluate and benchmark STT, LLM, and TTS/ASR components on accuracy, latency, naturalness, and robustness across accents, languages, and real-world audio conditions
• Work hands-on with STT, TTS, and ASR models — fine-tuning, evaluating, and improving them for production use cases
• Identify failure modes and edge cases across the pipeline (background noise, accents, interruptions, turn-taking, latency, pipeline-stage handoffs) and build systems to catch them before production
• Collaborate closely with engineering to integrate quality checks and automation into the voice agent development lifecycle within the Pipecat-based architecture
• Research and stay current with advances in voice AI, and bring in new techniques, models, and tools to improve pipeline performance
• Work directly with customers to understand real-world voice use cases and translate them into evaluation criteria and quality benchmarks
• Partner with product and engineering to define what "production-grade quality" means for voice agents and drive the team toward it

What We're Looking For

• 4–6 years of experience, with a specialization in voice AI systems and automated quality evaluation
• Hands-on experience with STT (Speech-to-Text), TTS (Text-to-Speech), and ASR (Automatic Speech Recognition) models
• Experience designing and building automated testing/evaluation frameworks for voice or speech systems
• Strong understanding of what drives voice AI quality — accuracy, latency, naturalness, and robustness to real-world variability
• Strong programming skills in Python; familiarity with Pipecat or similar voice pipeline/orchestration frameworks is a plus
• Understanding of STT → LLM → TTS pipeline architectures and the trade-offs involved at each stage
• Research mindset — comfortable exploring new models, techniques, and tools and translating them into practical improvements
• Excellent communication skills — this is a customer-facing role, and you'll regularly engage directly with customers to understand needs and validate quality expectations