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Senior Ai Intelligent Automation Engineeer Location - Remote Shift - 6.30 PM to 3.30 AM Job Type - Permanent JD We are seeking a highly skilled and innovative AI Senior Automation Engineer to design, develop, and implement intelligent automation solutions that accelerate enterprise digital transformation initiatives. This role will focus on leveraging Artificial Intelligence (AI), Generative AI, Machine Learning (ML), Robotic Process Automation (RPA), workflow orchestration, and cloud-native automation technologies to optimize business operations, enhance customer experiences, and improve operational efficiency across enterprise environments. The ideal candidate combines robust software engineering capabilities with deep expertise in AI-powered automation platforms, enterprise integration, DevSecOps practices, and scalable cloud architectures. The engineer will work closely with cross-functional teams including AI architects, cloud engineers, cybersecurity specialists, infrastructure teams, and business stakeholders to deliver end-to-end automation solutions aligned with Pelleras AIM (Advise, Implement, Manage) methodology. Required Qualifications - Bachelors or Masters degree in Computer Science, Information Technology, Engineering, or related field. - 6+ years of experience in software engineering, automation engineering, or AI engineering roles. - 3+ years of experience implementing enterprise automation solutions using AI/ML technologies. - Strong programming skills in Python, Java, JavaScript, or C#. - Experience with workflow automation and orchestration platforms. - Hands-on experience with REST APIs, microservices, and event-driven architectures. - Experience with cloud platforms such as AWS, Azure, or Google Cloud. - Strong understanding of DevOps, CI/CD, and Infrastructure as Code principles. - Experience working with databases including SQL, NoSQL, and vector databases. Preferred Skills - Experience with Generative AI frameworks such as LangChain, Semantic Kernel, or LlamaIndex. - Knowledge of LLM platforms including OpenAI, Azure OpenAI, Anthropic, or open-source LLMs. - Experience with RPA platforms such as UiPath, Automation Anywhere, Power Automate. - Familiarity with container orchestration technologies including Docker and Kubernetes. - Understanding of cybersecurity best practices and secure automation design. - Experience with observability and monitoring tools such as Prometheus, Grafana, ELK, or Splunk. - Exposure to enterprise IT environments including hybrid cloud and data center modernization initiatives. - AI governance, compliance, and responsible AI implementation knowledge. Key Responsibilities AI & Intelligent Automation Development - Design and implement AI-driven automation workflows for enterprise business processes. - Develop intelligent agents, copilots, chatbots, and workflow automation using Generative AI and LLM technologies. - Build scalable automation pipelines integrating AI, analytics, and enterprise systems. - Create reusable automation frameworks, APIs, and orchestration components. - Implement document intelligence, OCR, NLP, and computer vision automation solutions. Enterprise Automation & Integration - Integrate automation solutions with enterprise platforms such as ERP, CRM, ITSM, cloud platforms, and data systems. - Develop event-driven and API-based integrations using modern middleware and integration frameworks. - Automate infrastructure provisioning, CI/CD pipelines, cloud operations, and monitoring workflows. - Collaborate with infrastructure and cloud teams to modernize enterprise operations. AI Engineering & Data Solutions - Deploy and optimize machine learning and Generative AI models in production environments. - Implement Retrieval-Augmented Generation (RAG), vector databases, semantic search, and AI orchestration frameworks. - Fine-tune AI models and optimize prompt engineering strategies. - Ensure responsible AI governance, model observability, and performance monitoring. Cloud & DevSecOps Automation - Build automation solutions across AWS, Azure, Google Cloud, and hybrid cloud environments. - Implement Infrastructure as Code (IaC) using Terraform, Ansible, or CloudFormation. - Automate security compliance, vulnerability remediation, and operational workflows. - Support containerized and Kubernetes-based automation platforms. Collaboration & Leadership - Provide technical leadership and mentorship to automation and engineering teams. - Conduct architecture reviews, code reviews, and technical assessments. - Engage with clients and stakeholders to gather requirements and recommend AI automation strategies. - Participate in solution workshops, proofs of concept, and innovation initiatives. Soft Skills - Strong analytical and problem-solving capabilities. - Excellent communication and stakeholder management skills. - Ability to work in fast-paced enterprise transformation environments. - Strong collaboration and leadership .
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.