Test Automation Engineer

Senior Generative AI Engineer

Job Id: QX016

About Us:

The QX impact was launched with a mission to make AI accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them.

Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.

Job Summary:

We seek a highly experienced Senior Generative AI Engineer who focus on the development, implementation, and engineering of Gen AI applications using the latest LLMs and frameworks. This role requires hands-on expertise in Python programming, cloud platforms, and advanced AI techniques, along with additional skills in front-end technologies, data modernization, and API integration. The Senior Gen AI engineer will be responsible for building applications from the ground up, ensuring robust, scalable, and efficient solutions.

Responsibilities:

·        Build GenAI solutions such as virtual assistant, data augmentation, automated insights and predictive analytics

·        Design, develop, and fine-tune generative AI models (GANs, VAEs, Transformers).

·        Handle data preprocessing, augmentation, and synthetic data generation.

·        Work with NLP, text generation, and contextual comprehension tasks.

·        Develop backend services using Python or .NET for LLM-powered applications.

·        Build and deploy AI applications on cloud platforms (Azure, AWS, GCP).

·        Optimize AI pipelines and ensure scalability.

·        Stay updated with advancements in AI and ML.

Skills & Requirements:

• Strong knowledge of machine learning, deep learning, and NLP.
• Proficiency in Python, TensorFlow, PyTorch, and Keras.
• Experience with cloud services, containerization (Docker, Kubernetes), and AI model deployment.
• Understanding of LLMs, embeddings, and retrieval-augmented generation (RAG).
• Ability to work independently and as part of a team.
• Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
• 6+ years of experience in Gen AI, or related roles.
• Experience with AI/ML model integration into data pipelines.

Core Competencies for Generative AI Engineers:

1.      Programming & Software Development

a.      Python – Proficiency in writing efficient and scalable code with strong knowledge with NumPy, Pandas, TensorFlow, PyTorch and Scikit-learn.

b.      LLM Frameworks – Experience with Hugging Face Transformers, LangChain, OpenAI API, and similar tools for building and deploying large language models.

c.      API integration such as FastAPI, Flask, RESTful API, WebSockets or Django.

d.      Knowledge of Version Control, containerization, CI/CD Pipelines and Unit Testing.

2.      Vector Database & Cloud AI Solutions

a.      Pinecone, FAISS, ChromaDB, Neo4j

b.      Azure Redis/ Cognitive Search

c.      Azure OpenAI Service

d.      Azure ML Studio Models

e.      AWS (Relevant Services)

3.      Data Engineering & Processing

1. Handling large-scale structured & unstructured datasets.
2. Proficiency in SQL, NoSQL (PostgreSQL, MongoDB), Spark, and Hadoop.
3. Feature engineering and data augmentation techniques.

4.      NLP & Computer Vision

1. NLP: Tokenization, embeddings (Word2Vec, BERT, T5, LLaMA).
2. CV: Image generation using GANs, VAEs, Stable Diffusion.
3. Document Embedding – Experience with vector databases (FAISS, ChromaDB, Pinecone) and embedding models (BGE, OpenAI, SentenceTransformers).
4. Text Summarization – Knowledge of extractive and abstractive summarization techniques using models like T5, BART, and Pegasus.
5. Named Entity Recognition (NER) – Experience in fine-tuning NER models and using pre-trained models from SpaCy, NLTK, or Hugging Face.
6. Document Parsing & Classification – Hands-on experience with OCR (Tesseract, Azure Form Recognizer), NLP-based document classifiers, and tools like LayoutLM, PDFMiner.

5.      Model Deployment & Optimization

1. Model compression (quantization, pruning, distillation).
2. Deployment using Azure CI/CD, ONNX, TensorRT, OpenVINO on AWS, GCP.
3. Model monitoring (MLflow, Weights & Biases) and automated workflows (Azure Pipeline).
4. API integration with front-end applications.

6.      AI Ethics & Responsible AI

1. Bias detection, interpretability (SHAP, LIME), and security (adversarial attacks).

7.      Mathematics & Statistics

1. Linear Algebra, Probability, and Optimization (Gradient Descent, Regularization, etc.).

8.      Machine Learning & Deep Learning

a.      Expertise in supervised, unsupervised, and reinforcement learning.

a.      Proficiency in TensorFlow, PyTorch, and JAX.

b.      Experience with Transformers, GANs, VAEs, Diffusion Models, and LLMs (GPT, BERT, T5).

Personal Attributes:

• Strong problem-solving skills with a passion for data architecture.
• Excellent communication skills with the ability to explain complex data concepts to non-technical stakeholders.
• Highly collaborative, capable of working with cross-functional teams.
• Ability to thrive in a fast-paced, agile environment while managing multiple priorities effectively.

Why Join Us?

• Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
• Work on impactful projects that make a difference across industries.
• Opportunities for professional growth and continuous learning.
• Competitive salary and benefits package.

Ready to make an impact? Apply today and become part of the QX impact team!

• Minimum of 5 years of experience in B2B enterprise sales with atleast 1-2years in a start-up.
• Should have a proven track record of closing complex deals and managing large accounts.
• Strong understanding of the full sales lifecycle, from prospecting to closing, with expertise in consultative selling and solution-based sales
• Strong negotiation and deal-closing abilities, with the capacity to build trust and rapport with high-level stakeholders.
• Strong experience using CRM systems to track and manage sales pipelines, opportunities, and client interactions.
• Should have done a 0 to 1 sales growth story
• Must be handling West region currently and candidates from Mumbai preferred.

• Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience)
• Proven 2 to 12 years of professional experience in Node.js development
• Strong proficiency in JavaScript, including ES6+ syntax
• Expertise in designing and developing RESTful APIs and microservices architecture
• Experience with popular Node.js frameworks such as Express.js, Nest.js, or Hapi.js
• Experience in modern front-end technologies (e.g., HTML, CSS, JavaScript frameworks like React, Angular, or Vue.js)
• Solid understanding of asynchronous programming, event-driven architecture, and design patterns
• Extensive knowledge of database systems, both SQL and NoSQL (e.g., MongoDB, PostgreSQL, MySQL)
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform
• Familiarity with containerization technologies (e.g., Docker, Kubernetes)

1. 1. Experience with React JS, React Native, JavaScript including DOM Manipulation and the JavaScript object model.
   2. Thorough understanding of React Native and its core Principles.
   3. Hands on experience on React Native Framework at least 1 year.
   4. Understanding of native build tools like Xcode, Gradle etc.
   5. Capability to write Well-documented code with Javascript that is easily readable.
   6. Good Knowledge of HTML5, CSS.
   7. Familiarity with code versioning tools (Such as Git or SVN)
   8. Knowledge about Offline Storage, REST APIs, and document request model
   9. Familiarity with modern front-end build pipelines and tools.
   10. Experience with common front-end development tools such as Babel, Web pack, NPM and YARN etc.
   11. Experience with Native Mobile app deployment on App store and google play store.

Role

Being a part of the Products / Software Engineering team, this member is expected to work with the existing development team. Key responsibilities of this role include MS Tech stack-based applications as per the product roadmap / project scope. Coordinate with co-developers and contribute to all phases of the development lifecycle.

Experience

Around 4 years of experience in creating and implementing Web-based applications using

C#, ASP.net, Web API, MVC, Micro Services, JavaScript and SQL Server.

Familiarity or exposure to CI / CD, Dev Ops such as Dockers, containers, Azure, Pipeline is

highly recommended

Ability to work in an Agile, fast-paced environment, and learn rapidly.

Bachelor degree in computer science, computer engineering or similar.

Familiar with object-oriented development, design patterns and specifically in .NET

Framework (C#) with a strong background in web-based development and service-oriented

Architecture.

Expert in HTML, CSS, JavaScript, JQuery, JSON.

Writing clean, readable, and easily maintainable code.

Must have knowledge of project/task management tools like Jira,

Familiarity with Version Control like Bitbucket, Git etc.

Understanding of UI, cross-browser compatibility and web standards.

Build features and applications with responsive design

Good English communication skills, written and spoken.

Able to work with minimum supervision as well as perform under pressure and meet

Deadlines.

• Managing the solving of problems concerning the test automation infrastructure
• Understand and maintain Test Automation Frameworks.
• Follow the coding standards and code walk through.
• Maintain Automation Standards and Processes documentation.
• Write automated test scripts under the direction of the Test Automation Lead.
• Ability to work independently on tasks / modules assigned related to automation
• Monitoring of and reporting on the progress of the test automation process
• Reporting on the quality of the test object
• Raise risks on time and provide alternate solutions to mitigate the risk
• Advice and support for the implementation of all types of tools