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AI Engineer Responsibilities: LLM Model Optimization Lead fine-tuning and optimization of large language models (LLMs) to improve accuracy and robustness in call-center scenarios. Design and implement conversation pipelines and plugin architectures using LangChain and LangGraph for efficient, scalable query and retrieval workflows. Retrieval-Augmented Generation (RAG) & Knowledge-Based Construction Architect and build RAG workflows: set up vector stores, retrieval modules, and integrate them with LLMs to generate context-aware responses. Collect, clean, annotate, and preprocess datasets, design automated pipelines for ingestion and continuous knowledge base updates. System Integration & Engineering Develop production-grade Python services on Linux, writing clean, maintainable, and scalable code. Containerize and orchestrate model services using Docker and Kubernetes ; establish CI/CD pipelines for automated builds, tests, and deployments. Performance Monitoring & Continuous Iteration Integrate and optimize third-party speech and language services, developing custom connectors as needed. Implement monitoring and logging systems; analyze key metrics (latency, throughput, accuracy) and recommend performance improvements. Qualifications: Experience Minimum 5 years of experience in software development, with at least 2 years in the AI domain. Programming & Frameworks Expert in Python and at least one deep learning framework ( TensorFlow , PyTorch , or JAX ). Hands-on experience with LLM fine-tuning , prompt engineering , LangChain , and LangGraph . Data & Algorithms Strong understanding of vector embedding techniques and experience with tools such as Qdrant , FAISS , Annoy , or Pinecone . Proven ability to design and maintain end-to-end data pipelines (collection, cleaning, annotation, splitting). Systems & Deployment Minimum 1 year of production-level software development on Linux . Proficient in Docker and Kubernetes , with experience designing microservices architectures . Familiarity with CI/CD platforms (Jenkins, GitLab CI/CD, GitHub Actions) is a plus. Preferred Qualifications: Deep knowledge of vector database internals and operations (e.g., Qdrant , Milvus , Weaviate , Pinecone ). Experience deploying multi-tenant online services with auto-scaling. Familiarity with an additional backend language ( Go , C++ ) or frontend frameworks ( React , Vue ). Background in integrating AI into financial , e-commerce , or telecom call-center platforms . Publications in related fields or significant open-source contributions . MLOps Engineer Responsibilities: Design and maintain end-to-end ML/LLM system development and operations in production. Build CI/CD pipelines for AI model development and orchestration, enabling continuous delivery and automation of AI workloads. Manage the full lifecycle of generative AI models (GenAIOps) development, deployment, and operations. Deploy and optimize workloads across on-premise and cloud environments. Requirements : Minimum 2 years of experience in the AI domain. Hands-on experience with GPU infrastructure (e.g., H100, T4) and GPU stack management. Experience with model serving and orchestration frameworks such as Ray Serve. Strong background in CI/CD, automation, and integrating AI into enterprise applications. Familiarity with both on-premise and cloud deployment. Employee Benefits: Compensation: Annual salary reviews, performance-based bonuses, and housing loan support. Financial Wealth: 5% Provident Fund employer match and Employee Joint Investment Program (EJIP). Milestone Gifts: 5,000 – 10,000 THB cash allowance for major life events. Medical & Health: Premium IPD/OPD health insurance, accident insurance, and annual health check-ups. Wellness & Dental: 1,500 THB/month fitness subsidy and 2,000 THB/year dental allowance. Annual Leave: 8-14 days of Annual Vacation, 7 days of Personal Leave, plus Birthday Leave. Special Life Event Leave: Fully paid special leave for major life events (e.g., maternity, ordination, etc.). Daily Subsidies: 75 THB/day food allowance and a 15% cafe discount. Travel & Commuting: 1,000 THB/month parking & Grab Business for meetings. Learning & Growth: Dedicated Learning & Development budget for professional courses and skill training.
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.