Test Engineer - AI/ML,

About Us

We’re building the next generation of AI-powered business software, and we’re looking for people who want to shape that future with us. With Lumen, we’re reimagining how users interact with CRM — moving beyond screens, menus and dashboards to an intelligent interface where users can simply ask AI to take actions, retrieve knowledge, generate insights and get work done. With Agent Studio, we’re enabling businesses to build, test and deploy their own AI agents for real-world workflows. And with Invorto, we’re bringing AI to voice, allowing businesses to create intelligent voice agents tailored to their customer and operational use cases.

What makes this especially exciting is the stage and scale of the opportunity. You’ll get to work on genuinely hard problems across LLMs, agents, reasoning, orchestration, voice AI, evaluation, reliability and enterprise security — not as isolated experiments, but as products used in real business workflows. You’ll have the opportunity to build zero-to-one, own meaningful parts of the product end-to-end, work closely with customers, experiment rapidly, and see your work reach production at scale.

Why join now? Because the playbook for enterprise AI is still being written. You won’t just be implementing someone else’s roadmap — you’ll help define the product, architecture and experiences that become that playbook. Expect high ownership, fast iteration, hard technical and product problems, direct customer impact, and the chance to build AI systems that have to work reliably in the real world — not just in a demo.

About the Role

We are looking for a QA Engineer who specializes in testing agentic AI platforms. You will design and automate quality processes for systems that involve LLMs, autonomous agents, tool use and orchestration across Lumen and Agent Studio — ensuring that AI-driven workflows behave reliably, safely and predictably in production, not just in a demo.

What You’ll Do

• Design and build automated test suites and evaluation frameworks for agentic AI workflows, including multi-step and tool-calling behaviors.
• Use AI/LLM-based QA tools and evaluation frameworks to test model outputs, agent decisions and end-to-end task completion at scale.
• Define quality metrics and benchmarks for agent reliability, correctness, latency and safety, and track them over releases.
• Identify edge cases, failure modes and regressions specific to non-deterministic AI systems, and build automated checks to catch them early.
• Integrate automated agent/LLM testing into CI/CD pipelines to support fast, reliable iteration.
• Partner closely with AI/ML and backend engineers to reproduce issues, root-cause failures and validate fixes.
• Work with customers and customer-facing teams to understand real-world usage patterns and translate them into test scenarios.

What We’re Looking For

• 2–4 years of QA/test automation experience, including hands-on work testing agentic AI or LLM-based platforms.
• Practical experience using AI-focused QA/evaluation tools to test agent behavior, prompts and model outputs.
• Strong scripting/automation skills (Python preferred) to build and maintain test frameworks.
• Understanding of how LLM-based agents work — tool calling, orchestration, memory, reasoning chains — well enough to design meaningful test cases.
• Comfort working with non-deterministic systems and designing evaluation approaches beyond traditional pass/fail testing.
• Strong communication skills — this is a customer-facing role, and you will be expected to clearly articulate technical concepts, decisions and trade-offs to both technical and non-technical stakeholders, including customers.

Good to Have

• Experience testing voice AI or real-time conversational systems.
• Familiarity with CRM or enterprise SaaS platforms.
• Exposure to enterprise security or compliance testing for AI systems.

Required Skills:-

• 4+ years of experience in Software Testing (Manual & Automation).
• Strong experience with Selenium or Playwright.
• Hands-on experience in API Testing (Postman, REST Assured, Swagger, etc.).
• Experience with CI/CD pipelines (Jenkins, GitLab CI, Azure DevOps, GitHub Actions).
• Strong understanding of Functional, Regression, and Non-functional Testing.
• Excellent analytical and debugging skills.

AI-Specific Skills

• Hands-on experience in GenAI / AI Testing.
• Experience testing LLM-based applications.
• Strong understanding of prompt engineering and prompt validation.
• Knowledge of LLM behavior, model variability, and non-deterministic outputs.
• Experience validating AI outputs for accuracy, hallucinations, bias, and safety.
• Test data management for AI applications.
• Understanding of Responsible AI testing concepts.

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.

AI Engineer

We are seeking an AI Engineering specialist focused on AI evaluation, and continuous quality improvement for Ezra MetLife's employee-facing AI platform. This role will establish and scale the testing strategy for enterprise AI agents, ensuring high response quality, reliability, and production readiness. The engineer will build automated regression testing framework (preferred Playwright ), define AI evaluation methodologies, analyze AI performance metrics, and partner with engineering teams to continuously improve answer quality, grounding accuracy, and customer experience. This position is critical to enabling confidence as Ezra expands its AI agent portfolio and employee-facing capabilities.

Required Skills & Experience

• C# and .NET development experience

• Experience with at least one AI evaluation framework (e.g., prompt evaluation, RAG evaluation, LLM quality assessment)

• Microsoft Agent Framework (preferred) or similar enterprise agent frameworks

• Experience with Azure OpenAI / Azure AI Foundry

• Microsoft 365 Agent SDK

• Azure AI Search, RAG pipelines, and retrieval quality testing

• Infrastructure as Code using Terraform

• Experience building automated testing and AI quality validation processes

• Familiarity with telemetry analysis, AI observability, and performance measurement

• Strong analytical skills with a passion for improving AI response quality and reliability

Skills: AI Agents~Core .NET Technologies~C# 5.0

Experience Required: 10 & Above

Location: Hyderabad :5+ relevant exp in AI + .NET

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. 

• Web Application Testing: Design, document, and execute comprehensive functional test plans and test cases for complex, highly interactive web applications, ensuring they meet specified requirements and provide an excellent user experience.
• Backend API Testing: Possess deep expertise in validating backend RESTful and/or SOAP APIs. This includes testing request/response payloads, status codes, data integrity, security, and robust error handling mechanisms.
• Data Validation with SQL: Write and execute complex SQL queries (joins, aggregations, conditional logic) to perform backend data checks, verify application states, and ensure data integrity across integration points.
• I Automation (Playwright & TypeScript):
• Design, develop, and maintain robust, scalable, and reusable UI automation scripts using Playwright and TypeScript.
• Integrate automation suites into Continuous Integration/Continuous Deployment (CI/CD) pipelines.
• Implement advanced automation patterns and frameworks (e.g., Page Object Model) to enhance maintainability.
• Prompt-Based Automation: Demonstrate familiarity or hands-on experience with emerging AI-driven or prompt-based automation approaches and tools to accelerate test case generation and execution.
• API Automation: Develop and maintain automated test suites for APIs to ensure reliability and performance.
• JMeter Proficiency: Utilize Apache JMeter to design, script, and execute robust API load testing and stress testing scenarios.
• Analyze performance metrics, identify bottlenecks (e.g., response time, throughput), and provide actionable reports to development teams.
• Experience: 4+ years of professional experience in Quality Assurance and Software Testing, with a strong focus on automation.
• Automation Stack: Expert-level proficiency in developing and maintaining automation scripts using Playwright and TypeScript.
• Testing Tools: Proven experience with API testing tools (e.g., Postman, Swagger) and strong functional testing methodologies.
• Database Skills: Highly proficient in writing and executing complex SQL queries for data validation and backend verification.
• Performance: Hands-on experience with Apache JMeter for API performance and load testing.
• Communication: Excellent communication and collaboration skills to work effectively with cross-functional teams (Developers, Product Managers).
• Problem-Solving: Strong analytical and debugging skills to efficiently isolate and report defects.

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.

• 12 - 16 years of experience in Enterprise Software Product Engineering (Development/Quality) 
• Working experience with Enterprise SaaS product companies 
• 6+ years of experience in leading/managing multi-discipline activities - manual, automation, performance and security testing. 
• Experience with AI powered test automation frameworks like Playwright, TestRigor etc is preferable. 
• Experience with security and performance testing tools like BurpSuite, Locust, K6 etc   
• Strong experience in generating and presenting data/metric driven reports to exec/C-level stakeholders. 
• Self drive to achieve team and organization goals with high ROI 
• Result oriented collaborator and enabler of success. 
• Preferred: 
• Enterprise software experience withing the Life Sciences industry and good understanding of GxP requirements 
• Knowledge of cloud native, distributed architecture 

Responsibilities:

• Lead the overall strategy, execution, reporting of ValGenesis’s platform/integration testing activities 
• Own the strategic vision and establish the Software QA processes, tools, frameworks. Ensure, Monitor and Measure of the same in terms of rollout, adoption, results. 
• Change advocate of lean and efficient working – Processes, Tools, Resources. 
• Work with the engineering and cross-functional leaders along with the developers/testers to achieve continuous and incremental quality improvement across all products. 
• Own and deliver automation, security, performance testing frameworks/tools/strategies.  
• Enable the adoption of such tools/frameworks during development phase. 
• Build tools to monitor and generate metrics of all QA activities - test definition, execution, results, production incidents etc. 
• Build a strategy and deliver capabilities to fully automate computer software validation for all product releases. 
• Build and sustain high performance teams – Hiring, Performance and Talent Management 

Role Overview:

As an AI Executor/AI Automation Engineer, you will be responsible for designing and integrating AI capabilities into production systems using Python and key ML libraries. This role requires a strong backend development foundation and a proven track record of deploying AI use cases using tools like TensorFlow, Keras, or OpenAI APIs. You'll work cross-functionally to deliver scalable AI-driven solutions.

Key Responsibilities:

• Design and develop backend solutions using Python, with a focus on AI-driven features.
• Implement and integrate AI/ML models using tools like OpenAI, Hugging Face, or Lang Chain.
• Use core Python libraries (NumPy, Pandas, TensorFlow, Keras) to process data, train, or implement models.
• Translate business needs into AI use cases and deliver working solutions.
• Collaborate with product, engineering, and data teams to define integration workflows.
• Develop REST APIs and micro services to deploy AI components within applications.
• Maintain and optimize AI systems for scalability, performance, and reliability.
• Keep pace with advancements in the AI/ML landscape and evaluate tools for continuous improvement.

Required Skills & Qualifications:

• 2+ years of professional experience as an AI/ML Engineer, including strong backend development expertise in Python.
• Proficiency in libraries such as NumPy, Pandas, TensorFlow, and Keras
• Practical exposure to AI platforms/APIs (e.g., OpenAI, LangChain, Hugging Face)
• Solid understanding of REST APIs, micro services, and integration practices
• Ability to work independently in a remote setup with strong communication and ownership
• Excellent problem-solving and debugging capabilities
• Experience with the MERN stack will be an added advantage.