SDET- II at MindTickle

Pune, Maharashtra, India

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, SaaS, Sales EnablementIndustries

Requirements

Experience with LLM testing & evaluation tools: MaximAI, OpenAI Evals, TruLens, Promptfoo, LangSmith
Building LLM-powered apps: prompt pipelines, embeddings, RAG, AI workflows
CI/CD design for application + LLM testing
API, performance, and system testing
Git, Docker, and cloud platforms (AWS / GCP / Azure)
Bias, fairness, hallucination detection & AI safety testing
Mentorship and cross-functional leadership
Bachelor’s or Master’s in Computer Science, Engineering, or equivalent
4+ years in software development, SDET, or QA automation
Proficiency in GoLang, Java, or Python
Proven experience building test automation frameworks
Proven ability to design CI/CD pipelines with automated regression and evaluation testing
Hands-on exposure to LLMs, GenAI applications
2+ years of hands-on experience with LLM APIs and frameworks (OpenAI, Anthropic, Hugging Face)
Proficient in prompt engineering, embeddings, RAG, and LLM evaluation metrics
Strong analytical, leadership, and teamwork skills
Excellent communication and collaboration across teams

Responsibilities

Own the end-to-end qualification lifecycle for AI/LLM systems from ideation and implementation to CI/CD integration
Design and implement scalable automated test suites across unit, integration, regression, and system levels
Build and enhance frameworks to test, evaluate, and continuously improve complex AI and LLM workflows
Lead the design and automation of LLM-powered features, including prompt pipelines, RAG workflows, and AI-assisted developer tools
Develop evaluation pipelines to measure factual accuracy, hallucination rates, bias, robustness, and overall model reliability
Define and enforce metrics-driven quality gates and experiment tracking workflows to ensure consistent, data-informed releases
Collaborate with agile engineering teams, participating in design discussions, code reviews, and architecture decisions to drive testability and prevent defects early (“shift left”)
Develop monitoring and alerting systems to track LLM production quality, safety, and performance in real time
Conduct robustness, safety, and adversarial testing to validate AI behavior under edge cases and stress scenarios
Continuously improve frameworks, tools, and processes for LLM reliability, safety, and reproducibility
Mentor junior engineers in AI testing, automation, and quality best practices
Measure and improve Developer Experience (DevEx) through tools, feedback loops, and automation
Champion quality engineering practices across the organization, ensuring delivery meets business goals, user experience, cost of operations etc

Skills

Key technologies and capabilities for this role

LLMAI TestingCI/CDTest AutomationRAGPrompt PipelinesUnit TestingIntegration TestingRegression TestingAdversarial TestingMonitoringAgileCode ReviewEvaluation Metrics

Questions & Answers

Common questions about this position

What experience level is required for this SDET-II role?

The role requires 4+ years in software development, SDET, or QA automation, plus 2+ years of hands-on experience with LLM APIs and frameworks.

What programming languages are needed for this position?

Proficiency in GoLang, Java, or Python is required.

What specific AI and LLM skills are preferred?

Preferred skills include experience with LLM testing tools like MaximAI, OpenAI Evals, TruLens; building LLM-powered apps with prompt pipelines, embeddings, RAG; proficiency in prompt engineering, embeddings, RAG, and LLM evaluation.

What is the salary or compensation for this role?

This information is not specified in the job description.

Is this a remote position or does it require office work?

This information is not specified in the job description.

MindTickle

Sales readiness and enablement platform

About MindTickle

MindTickle provides sales readiness and enablement solutions through a platform that focuses on training sales teams using micro-learning, social interactions, and gamified methods. The platform delivers small, digestible learning content that engages users and enhances their training experience. MindTickle caters to a diverse range of clients, from small businesses to large enterprises, particularly in customer-centric industries like MedTech and technology. Unlike many competitors, MindTickle offers a subscription-based software as a service (SaaS) model, allowing clients to access their tools based on user needs and service levels. Key features of the platform include virtual coaching tools, data-driven insights, and readiness assessments, all aimed at improving sales skills and customer interactions. The company's goal is to continuously enhance sales capabilities and ensure teams are well-prepared to deliver exceptional customer experiences.

San Francisco, CaliforniaHeadquarters

2012Year Founded

$273.6MTotal Funding

SERIES_ECompany Stage

Data & Analytics, Enterprise Software, EducationIndustries

501-1,000Employees

Risks

Economic uncertainty may lead to reduced budgets for sales readiness solutions.

Rapid AI advancements require continuous innovation to maintain competitive edge.

Integration challenges from acquiring Enable Us could disrupt service delivery.

Differentiation

MindTickle offers a unique blend of gamified and data-driven sales training.

The platform integrates virtual coaching and readiness assessments for comprehensive sales enablement.

MindTickle's SaaS model allows flexible, scalable solutions for diverse business needs.

Upsides

Recognition as a leader in revenue enablement boosts MindTickle's market credibility.

Generative AI Copilot enhances sales training, aligning with current AI trends.

74% customer growth and 233% ARR increase highlight strong market demand.

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