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- Tasks: Architect and deploy scalable AI systems, optimising performance and integrating with enterprise tools.
- Company: Join HCLTech, a $13+ billion global tech leader with a startup mindset and innovative culture.
- Benefits: Enjoy flexible work options, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a team that values ideas and drives impactful change in the tech industry.
- Qualifications: 5–8 years in AI/ML, strong Python skills, and experience with cloud platforms and vector databases.
- Other info: Mentorship opportunities available for junior engineers and a collaborative work environment.
The predicted salary is between 43200 - 72000 £ per year.
We are a $13+ billion global technology company, home to more than 224,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud, and AI, powered by a broad portfolio of technology services and products. HCLTech is a globally recognized leader in the Tech and IT industry, but we’ve never forgotten the startup mindset that got us here. We’ve always approached our work with an idea-first attitude because every one of our accomplishments — no matter how big or small — can be traced back to an idea’s single spark. It’s that spark — that inner drive — that sets our people apart from our competitors. It enables us not just to pull off game-changing feat after game-changing feat but to better our world in the process. We want you to find your spark. Because that’s what drives you to be better, be more and ultimately, be more fulfilled.
Detailed JD:
- Architect and deploy scalable AI systems leveraging LLMs (GPT, LLaMA, Claude, etc.)
- Build and fine-tune SLMs/LLMs using domain-specific data (e.g., ITSM, security, operations)
- Design and optimize Retrieval-Augmented Generation (RAG) pipelines with vector DBs (e.g., FAISS, Chroma, Weaviate, Pinecone)
- Develop agent-based architectures using LangGraph, AutoGen, CrewAI, or custom frameworks
- Integrate AI agents with enterprise tools (ServiceNow, Jira, SAP, Slack, etc.)
- Optimize model performance (quantization, distillation, batching, caching)
- Collaborate with DevOps and MLOps teams to build CI/CD pipelines for models and agents
- Conduct code and research reviews, mentor junior engineers, and contribute to technical strategy
- 5–8 years of hands-on experience in AI/ML/Deep Learning
- Strong coding skills in Python (must), familiarity with Node.js, Go, or Rust is a plus
- Proficient with PyTorch or TensorFlow
- Deep understanding of transformer architectures, embeddings, and attention mechanisms
- Experience with LangChain, Transformers (HuggingFace), or LlamaIndex
- Working knowledge of LLM fine-tuning (LoRA, QLoRA, PEFT) and prompt engineering
- Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Chroma)
- Cloud experience on Azure, AWS, or GCP (Azure preferred)
- Experience with Kubernetes, Docker, and scalable microservice deployments
- Experience integrating with REST APIs, webhooks, and enterprise systems (ServiceNow, SAP, etc.)
- Solid understanding of data pipelines, ETL, and structured/unstructured data ingestion
Contact Detail:
HCLTech Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AUTOMATION ARCHITECT
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and machine learning, particularly focusing on LLMs and their applications. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Engage with online communities and forums related to AI and automation. Networking with professionals in the industry can provide valuable insights and potentially lead to referrals for positions at HCLTech.
✨Tip Number 3
Consider contributing to open-source projects or creating your own projects that showcase your skills in Python, AI frameworks, and cloud technologies. This practical experience can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your previous experiences with scalable AI systems and how you've optimised model performance. Be ready to share specific examples that highlight your problem-solving skills and technical expertise.
We think you need these skills to ace AUTOMATION ARCHITECT
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI, ML, and Deep Learning. Focus on specific projects where you've architected or deployed scalable AI systems, and mention any hands-on experience with LLMs and vector databases.
Craft a Compelling Cover Letter: In your cover letter, express your passion for technology and innovation. Discuss how your background aligns with the company's startup mindset and their focus on idea-driven accomplishments. Mention specific technologies and frameworks you’ve worked with that are relevant to the role.
Showcase Your Technical Skills: Clearly list your technical skills, especially in Python, PyTorch, TensorFlow, and any experience with cloud platforms like Azure, AWS, or GCP. Highlight your familiarity with tools like LangChain and your understanding of transformer architectures.
Prepare for Technical Questions: Anticipate technical questions related to AI/ML concepts, coding challenges, and system design. Be ready to discuss your experience with CI/CD pipelines, model optimization techniques, and integration with enterprise tools during potential interviews.
How to prepare for a job interview at HCLTech
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with AI/ML and deep learning. Highlight specific projects where you've architected or deployed scalable AI systems, especially using LLMs. This will demonstrate your capability to handle the technical demands of the role.
✨Familiarise Yourself with Relevant Tools
Make sure you know the tools and technologies mentioned in the job description, such as PyTorch, TensorFlow, and vector databases like FAISS or Pinecone. Being able to speak confidently about these tools will show that you're ready to hit the ground running.
✨Prepare for Problem-Solving Questions
Expect to face scenario-based questions that assess your problem-solving skills. Think about how you would design and optimise RAG pipelines or integrate AI agents with enterprise tools. Practising these scenarios can help you articulate your thought process clearly.
✨Demonstrate Your Collaborative Spirit
Since the role involves collaboration with DevOps and MLOps teams, be ready to discuss your experience working in cross-functional teams. Share examples of how you've mentored junior engineers or contributed to technical strategy, showcasing your leadership and teamwork skills.
