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Job Description Ciklum is looking for a Senior Artificial Intelligence/Machine Learning Engineer to join our team full-time in Brazil. We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live. About The Role As a Senior Artificial Intelligence/Machine Learning Engineer, become a part of a cross-functional development team engineering experiences of tomorrow. This role is responsible for developing and enhancing enterprise Generative AI capabilities within the MALTS platform, accelerating AI adoption through reusable frameworks, agentic services, and self-service platform components. The engineer will contribute to the development of scalable GenAI, Data Science, and AI/ML lifecycle capabilities that enable faster delivery of business solutions across Consumer, Banking, and Wealth organizations. This is a hands-on software engineering role focused on building enterprise-grade Generative AI, Data Science, and AI Platform capabilities within client's strategic AI ecosystem. The engineer will work as an individual contributor responsible for designing, developing, and delivering reusable GenAI platform services, frameworks, APIs, and application components that support AI model development, deployment, inferencing, automation, and governance. The successful candidate will partner with senior engineers, architects, product owners, and data scientists to develop scalable, secure, and resilient solutions leveraging modern AI frameworks, cloud-native technologies, distributed computing platforms, and enterprise engineering practices. This role is ideal for an engineer passionate about Generative AI, application development, platform engineering, automation, and building reusable capabilities that accelerate enterprise AI adoption. Responsibilities Develop and enhance enterprise Generative AI platform capabilities, reusable services, and self-service tools Design and build AI-powered applications, agentic workflows, RAG solutions, and MCP-enabled services Develop scalable APIs, microservices, and platform components supporting AI/ML lifecycle management Build and maintain frameworks supporting model development, fine-tuning, deployment, inferencing, monitoring, and observability Implement event-driven and streaming solutions leveraging technologies such as Kafka and distributed processing platforms Contribute to CI/CD pipelines, automation frameworks, testing strategies, and DevOps practices Collaborate with platform engineers, architects, data scientists, and business stakeholders to deliver new capabilities Participate in design discussions, code reviews, sprint planning, story refinement, and estimation activities Ensure solutions meet enterprise standards for security, scalability, governance, resiliency, and operational excellence Support platform observability, monitoring, and performance optimization initiatives Continuously evaluate emerging AI technologies and contribute innovative solutions to enhance platform capabilities Core Engineering Responsibilities: Develop code and automated tests to deliver stories and requirements meeting quality and compliance standards Participate in application design leveraging data, application, integration, and platform architecture patterns Collaborate in requirement analysis, story refinement, and solution design activities Estimate and deliver assigned work within Agile development cycles Build agentic applications, AI assistants, workflow automation capabilities, and event-driven services using Kafka, containers, and MCP architectures Deliver secure, scalable, observable, and resilient software solutions aligned with enterprise standards Troubleshoot, optimize, and maintain platform services to ensure operational excellence Requirements Bachelor’s or master’s degree in computer science, Engineering, Data Science, or a related technical discipline 6+ years of software engineering experience with strong expertise in Python-based application development Experience developing AI/ML, Data Science, Data Engineering, or analytics applications in enterprise environments Strong understanding of modern Generative AI and Data Science platform architectures, including compute-storage separation, virtual environments, containers, Jupyter, and VS Code-based development Hands-on experience developing AI/ML and GenAI solutions using modern frameworks and tools Experience building scalable REST APIs and microservices using FastAPI or similar frameworks Experience developing applications leveraging vector stores, inference services, model-serving technologies, and AI orchestration frameworks Strong Python programming skills with experience building production-grade applications and reusable libraries Experience with AI/ML lifecycle management frameworks such as MLFlow, Kubeflow, model deployment, fine-tuning, and inference frameworks Experience building applications with API Gateway integration, JWT-based authentication, and enterprise security controls Understanding of metadata management, data lineage, governance principles, and semantic layer concepts Experience working within large-scale engineering organizations utilizing Git-based development, CI/CD pipelines, automated testing, and collaborative development practices Familiarity with cloud-native development, containers, Kubernetes, and distributed computing environments Core Skills: Python Generative AI / LLMs RAG & Agentic AI MCP Data Engineering Kubernetes & Containers Cloud Engineering CI/CD & DevSecOps Kafka/Event Streaming APIs & Microservices AI Platform Engineering Desirable Experience developing Retrieval-Augmented Generation (RAG) solutions Experience building MCP servers, AI agents, and multi-agent orchestration frameworks Knowledge of LLM integration, prompt engineering, model evaluation, and AI observability Familiarity with enterprise AI governance, responsible AI, metadata, and data quality concepts Exposure to enterprise-scale Generative AI platforms and self-service developer ecosystems What`s in it for you? Care: your mental and physical health is our priority. We ensure comprehensive company-paid medical insurance and mental health programs, 5 undocumented sick-leave days per year Tailored education path: boost your skills and knowledge with our regular internal events (meetups, conferences, workshops), Udemy license, language courses and company-paid certifications Growth environment: share your experience and level up your expertise with a community of skilled professionals, locally and globally Long-term employment with 20 working-days paid vacation and local bank holidays Flexibility: 100% remote work mode Opportunities: we value our specialists and always find the best options for them. Our Internal Mobility Program helps change a project if needed to help you grow, excel professionally and fulfill your potential Global impact: work on large-scale projects that redefine industries with international and fast-growing clients Welcoming environment: feel empowered with a friendly team, open-door policy, informal atmosphere within the company and regular team-building events About Us At Ciklum, we are always exploring innovations, empowering each other to achieve more, and engineering solutions that matter. With us, you’ll work with cutting-edge technologies, contribute to impactful projects, and be part of a One Team culture that values collaboration and progress. As we expand into Latin America, every Ciklumer is helping to shape our story. Collaborate with seasoned experts and make a global impact backed by two decades of industry leadership. Explore, empower
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.