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Role description Primary Skills: Agentic AI, Pytorch, RAG, ML, Gen AI Description: Key Responsibilities Build and deploy scalable LLM, RAG, and agent-based systems Architect LLM inference and deployment pipelines Optimize models for efficient and cost-effective production Collaborate with data science, research, and product teams Ensure clean code, testing, reproducibility, and CI/CD Mentor junior engineers and drive engineering best practices Ensure ethical, secure, and responsible AI development Required Skills Advanced Python with solid fundamentals in NumPy, Pandas, scikit-learn Deep learning expertise in PyTorch / TensorFlow Hands-on with LLM frameworks: Hugging Face Transformers, LangChain (prompting & fine-tuning) Robust experience with Agentic AI frameworks: AutoGen, CrewAI, LangGraph Expertise in RAG pipelines, semantic search, vector databases Solid software engineering practices: microservices, TDD, concurrency Ability to rapidly prototype and productionize GenAI solutions Good-to-Have Skills Model optimization: Quantization (GPTQ, AWQ), pruning, distillation Multimodal AI (text, vision, audio): CLIP, BLIP, Whisper, LLaVA LLM serving using FastAPI and vector DBs (FAISS, Pinecone, Chroma) CI/CD pipelines, Airflow, Docker, Kubernetes / Helm Cloud AI deployments on AWS / Azure / GCP (e.g., SageMaker) MLOps & tracking: Git, MLflow Data pipelines & ELT/ETL using Snowflake Skills Python, PyTorch, Agentic AI, RAG About UST UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the worlds best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients organizations. With over 30,000 employees in 30 countries, UST builds for boundless impacttouching billions of lives in the process. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.