At a Glance
- Tasks: Lead the development of cutting-edge Generative AI applications and collaborate on innovative projects.
- Company: Join a forward-thinking tech company at the forefront of AI innovation.
- Benefits: Attractive salary, health perks, remote work options, and opportunities for professional growth.
- Other info: Dynamic team environment with significant career advancement potential.
- Why this job: Be a pioneer in Generative AI and shape the future of technology.
- Qualifications: 6-10 years in apps development with strong AI/ML foundations and programming skills.
The predicted salary is between 80000 - 100000 £ per year.
Experience 6-10 years of relevant experience in Apps Development or systems analysis role.
Core AI/ML Foundations
- Strong foundational knowledge in GenAI, Machine Learning (ML) modeling, Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and Large Language Models (LLMs).
- Generative AI and LLM expertise.
LLM Proficiency
- Extensive hands-on experience with leading LLMs such as Google Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-source LLMs.
- Critical deep working knowledge and hands-on experience with Retrieval-Augmented Generation (RAG) pipelines, including advanced RAG techniques and their detailed implementation.
- Proven ability to build, tune, and deploy LLM-based applications using platforms like Vertex AI, Hugging Face, and others.
- Expertise in developing robust prompt engineering strategies, prompt tuning, and creating reusable prompt templates.
- Hands-on experience with agentic framework-based use case implementation.
- Working knowledge of guardrails and methodologies for assessing the performance and safety of GenAI features.
Programming and Data Engineering
- Strong programming proficiency in Python is a must, including extensive experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex.
- Proficiency in integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration tools.
- Hands-on experience with various vector databases (e.g., PG Vector, Pinecone, Mongo Atlas, Neo4j) for efficient data storage and retrieval; experience dealing with large amounts of unstructured data and designing solutions for high-throughput processing.
Deployment and MLOps
- Critical hands-on experience deploying GenAI-based models to production environments.
- Strong understanding and practical experience with MLOps principles, model evaluation, and establishing robust deployment pipelines.
- Strong expertise in CI/CD principles and tools (e.g., Jenkins, GitLab CI, Azure DevOps, ArgoCD) for automated builds, testing, and deployments.
Cloud & Containerization
- Proven experience with container orchestration platforms like OpenShift or Kubernetes for deploying, managing, and scaling containerized applications in a cloud-native environment.
Gen AI Lead employer: Virtusa
As a leading innovator in the field of Generative AI, our company offers an exceptional work environment that fosters creativity and collaboration. Located in a vibrant tech hub, we provide our employees with extensive growth opportunities through continuous learning and hands-on experience with cutting-edge technologies. Our inclusive culture prioritises employee well-being and encourages a healthy work-life balance, making us an ideal employer for those seeking meaningful and rewarding careers in AI.
StudySmarter Expert Advice🤫
We think this is how you could land Gen AI Lead
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that Gen AI Lead role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with LLMs and GenAI. We love seeing hands-on experience, so make sure to highlight your work with tools like Hugging Face and Vertex AI.
✨Tip Number 3
Prepare for the interview! Brush up on your knowledge of MLOps and deployment pipelines. We want to see that you can talk the talk and walk the walk when it comes to deploying GenAI models.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for talent that fits the bill for roles like Gen AI Lead.
We think you need these skills to ace Gen AI Lead
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in GenAI and LLMs. We want to see how your skills align with the job description, so don’t be shy about showcasing your relevant projects and achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit for the Gen AI Lead role. Share your passion for AI and how your background makes you a strong candidate. Keep it engaging and personal!
Showcase Your Technical Skills:We’re looking for hands-on experience, so make sure to include specific examples of your work with Python, LLMs, and MLOps. Highlight any projects where you’ve deployed models or worked with cloud technologies.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your materials and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Virtusa
✨Know Your GenAI Inside Out
Make sure you brush up on your knowledge of Generative AI and Large Language Models. Be ready to discuss your hands-on experience with models like Google Gemini and OpenAI. Prepare examples of how you've implemented advanced RAG techniques and the impact they had on your projects.
✨Show Off Your Programming Skills
Since strong programming proficiency in Python is a must, be prepared to talk about your experience with libraries like Pandas, NumPy, and TensorFlow. You might even want to bring along a project or two that showcases your coding skills and how you've integrated generative AI with enterprise applications.
✨Demonstrate MLOps Knowledge
Familiarise yourself with MLOps principles and be ready to discuss your experience deploying GenAI models in production. Highlight any CI/CD tools you've used, like Jenkins or Azure DevOps, and explain how you've established robust deployment pipelines in your previous roles.
✨Prepare for Technical Questions
Expect technical questions that dive deep into your understanding of AI fundamentals, including NLP and neural networks. Practice explaining complex concepts in simple terms, as this will demonstrate your mastery and ability to communicate effectively with both technical and non-technical stakeholders.
