🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
PFB Job description and kindly connect and let me know if interested or Share your CV on or if you have any references it will be helpful. Responsibilities: - Collaborate with cross-functional teams to understand business requirements and identify opportunities to apply Agentic AI and Generative AI (GenAI) solutions to solve complex enterprise problems. - Design, develop, and implement advanced GenAI and Agentic AI systems, including ReAct agents (Reasoning + Acting frameworks), multi-agent architectures, and autonomous AI workflows. - Build and deploy intelligent AI-powered chatbots and conversational agents using LLMs, tool-calling frameworks, retrieval-augmented generation (RAG), memory modules, and agent orchestration patterns. - Ensure consistency, reliability, and alignment in AI-generated outputs through prompt engineering, evaluation frameworks, guardrails, and monitoring mechanisms. - Develop and implement machine learning models and algorithms to support GenAI applications, including fine-tuning, embeddings, and hybrid AI architectures. - Perform data cleaning, preprocessing, and feature engineering to prepare structured and unstructured data for machine learning and GenAI pipelines. - Collaborate with data engineers to design efficient data pipelines and integrate ML/LLM systems into scalable production environments. - Validate and evaluate model and agent performance using appropriate metrics (accuracy, latency, hallucination rate, consistency scoring, human evaluation frameworks). - Develop and deploy production-ready AI applications using object-oriented programming principles, ensuring modularity, scalability, maintainability, and robustness. - Implement containerized AI solutions using Docker and Kubernetes for orchestration, scaling, and cloud-native deployments. - Design and implement tool-augmented agents, API-integrated workflows, and autonomous decision-making systems using modern AI agent frameworks. - Create dashboards, reports, and visualizations to communicate AI insights and business impact clearly to technical and non-technical stakeholders. - Continuously stay updated with advancements in GenAI, Agentic AI, multi-agent systems, LLM orchestration, and emerging AI frameworks, recommending innovative approaches to enhance enterprise AI capabilities. Requirements: - Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. - 7+ years of relevant technical/technology experience, with a focus on GenAI projects. - Strong programming skills in languages such as Python, R, or Scala. - Proficiency in machine learning libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn. - Experience with data preprocessing, feature engineering, and data wrangling techniques. - Solid understanding of statistical analysis, hypothesis testing, and experimental design. - Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud. - Knowledge of data visualization tools and techniques. - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. - Ability to work in a fast-paced and dynamic environment. - Experience with object-oriented programming languages such as Java, C++, or C#. Experience developing and deploying machine learning applications in production environments. - Understanding data privacy and compliance regulations. - Relevant certifications in data science or GenAI technologies. - Development experience in system designing, proven track record of software delivery through all phases of development, critical thinking, ability to clearly communicate, present and lead. Nice to Have Skills: - Experience with Azure AI Search, Azure Doc Intelligence, Azure OpenAI, AWS Textract, AWS Open Search, AWS Bedrock. - Familiarity with LLM backed agent frameworks such as Autogen, Langchain, Langgraph Semantic Kernel, etc. - Experience in chatbot design, frontend and development. - Certification of cloud or Genai - Designed and implemented enterprise-grade GenAI solutions using Databricks Mosaic AI, enabling scalable LLM deployment and governance. - Built Retrieval-Augmented Generation (RAG) pipelines using Mosaic AI Vector Search and Foundation Models for domain-specific knowledge querying. - Fine-tuned and deployed LLMs using Mosaic AI Model Serving, optimizing inference latency and cost. - Implemented secure LLM workflows with Unity Catalog governance and model tracking via MLflow. - Robust background in the Healthcare domain, with deep understanding of Payer operations and working knowledge of Provider ecosystems. - Experience in consulting engagements, including direct interaction with client stakeholders and managing client relationships. - Demonstrated leadership experience managing and mentoring teams of 510 members. If you are passionate about GenAI technologies and have a proven track record in data science, join PwC US - Acceleration Center and be part of a dynamic team .
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.