At a Glance
- Tasks: Build innovative GenAI applications and design architectures for large-scale data handling.
- Company: Join a leading tech firm focused on cutting-edge AI solutions.
- Benefits: Attractive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with exciting projects and career advancement potential.
- Why this job: Be at the forefront of AI technology and make a real difference in the industry.
- Qualifications: Expertise in Python and experience with GenAI frameworks required.
The predicted salary is between 63000 - 77000 £ per year.
- Long Description
- ________________________________________
Key Responsibilities
- 1. Application Development: Build Gen AI applications from scratch using frameworks like Autogen (applied or acquired), Crew. ai, Lang Graph, Llama Index, and Lang Chain.
- 2. Python Programming: Develop high-quality, efficient, and maintainable Python code for Gen AI solutions.
- 3. Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data.
- 4. Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models.
- 5. Fine-tune SLM(Small Language Model) for domain specific data and use cases.
- 6. Front-End Integration: Implement user interfaces using front-end technologies like React, Streamlit, and AG Grid, ensuring seamless integration with Gen AI backends.
- 7. Data Modernization and Transformation: Design and implement data modernization and transformation pipelines to support Gen AI applications.
- 8. Fine-Tuning LLMs: Apply fine-tuning techniques such as PEFT, QLo RA, and Lo RA to optimize LLMs for specific use cases.
- 9. LLMOps Implementation: Set up and manage LLMOps pipelines for continuous integration, deployment, and monitoring.
- 10. Responsible AI Practices: Ensure ethical AI practices are embedded in the development process.
- 11. innovation.
- Required Skills
- 1. Python Programming: Deep expertise in Python for building Gen AI applications and automation tools.
- 2. Productionization of Gen AI application beyond Po Cs – Using scale frameworks and tools such as Pylint, Pyrit etc.
- 3. LLM Frameworks: Proficiency in frameworks like Autogen, Crew. ai, Lang Graph, Llama Index, and Lang Chain.
- 4. Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data.
- 5. Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models.
- 6. Fine-tune SLM(Small Language Model) for domain specific data and use cases.
- 7. Prompt injection fallback and RCE tools such as Pyrit and HAX toolkit etc.
- 8. Anti-hallucination and anti-gibberish tools such as Bleu etc.
- 9. Front-End Technologies: Strong knowledge of React, Streamlit, AG Grid, and Java Script for front-end development.
- 10. Cloud Platforms: Extensive experience with Azure, GCP, and AWS for deploying and managing Gen AI applications. (any two cloud exp.)
- 11. Fine-Tuning Techniques: Mastery of PEFT, QLo RA, Lo RA, and other fine-tuning methods. (any one is fine)
- 12. LLMOps: Strong knowledge of LLMOps practices for model deployment, monitoring, and management.
- 13. Responsible AI: Expertise in implementing ethical AI practices and ensuring compliance with regulations.
- 14. RAG and Modular RAG: Advanced skills in Retrieval-Augmented Generation and Modular RAG architectures.
- 15. Data Modernization: Expertise in modernizing and transforming data for Gen AI applications.
- 16. OCR and Document Intelligence: Proficiency in OCR and document intelligence using cloud-based tools.
- 17. API Integration: Experience with REST, SOAP, and other protocols for API integration.
- 18. Data Curation: Expertise in building automated data curation and preprocessing pipelines.
- 19. Technical Documentation: Ability to create clear and comprehensive technical documentation.
- 20. Collaboration and Communication: Strong collaboration and communication skills to work effectively with cross-functional teams.
Target Companies – Quantiphi, Datastax, Coforge, HCL, Accenture, Fractal.
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Sr Application Developer employer: Worky
Goldman Sachs is an exceptional employer, offering a dynamic work environment where innovation and collaboration thrive. As a VP in Site Reliability Engineering, you will benefit from a culture that prioritises professional growth, with ample opportunities to lead critical projects and enhance your skills in a fast-paced financial services setting. Located in a vibrant city, the company provides competitive benefits and a commitment to employee well-being, making it an ideal place for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Sr Application Developer
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Worky or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Worky.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Worky.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Worky that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Sr Application Developer
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Worky.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Worky and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Worky
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Worky uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
