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Key Skills: Python, Java, Terraform, Ansible, AWS, Docker, Kubernetes, TensorFlow, PyTorch, Prometheus Good to Have Skills: Experience with cloud platforms like Azure and GCP, proficiency in Scikit-learn ML framework, knowledge of observability tools like Grafana and ELK stack, familiarity with CloudFormation for infrastructure automation, understanding of Spinnaker for deployment management, and experience with intelligent agents for workflow automation and decision-making processes. Roles & Responsibilities: Design and implement CI/CD pipelines, infrastructure-as-code frameworks, and container orchestration strategies leveraging various DevOps tools.Lead the architecture, deployment, and management of cloud infrastructure in AWS while establishing best practices for reliability and scalability.Drive the adoption of AI and machine learning capabilities within DevOps workflows including intelligent monitoring and predictive analytics.Lead the integration of intelligent agents for workflow automation, decision-making, and process optimization across development environments.Develop AI-powered observability solutions to monitor, analyze, and proactively manage application and infrastructure health using advanced techniques.Work closely with cross-functional teams including engineering, product, and operations to identify automation opportunities and deliver solutions.Stay abreast of emerging AI/ML technologies, frameworks, and industry trends while driving continuous improvement initiatives.Provide hands-on technical guidance to a team of software and DevOps engineers fostering innovation and continuous learning.Conduct code reviews, architectural assessments, and design discussions to uphold engineering excellence standards across the organization.Experience Required: 5+ years in AI/ML engineering with proven expertise in agent-based systems and automation, formal training or certification on software engineering concepts. .
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.