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Requirements and responsibilities
Role - Senior AI EngineerArchitect and build intelligent enterprise solutionsDesign and deliver scalable, secure, and production-ready AI-driven solutions that solve complex business challenges and create measurable impact.You will assess existing systems and processes to identify opportunities for modernization, optimization, and AI-led transformation.Lead AI-enabled engineering deliveryYou will build and deploy AI-powered applications using modern engineering practices, automation frameworks, and AI-assisted development tools.You will integrate AI capabilities into enterprise ecosystems through APIs, middleware, and cloud-native architectures.You will create reusable frameworks and scalable engineering patterns that accelerate adoption across multiple business functions.Drive delivery excellenceYou will lead rapid, iterative delivery through agile execution, experimentation, automation, and continuous feedback.You will establish strong DevOps and CI/CD practices to support efficient deployment, monitoring, and lifecycle management.You will ensure technical quality through documentation, automated validation, governance, and operational readiness.Collaborate and influenceYou will partner with business leaders, product teams, security, compliance, and architecture stakeholders to deliver robust solutions.You will communicate technical direction, solution trade-offs, and implementation strategies clearly to both technical and non-technical audiences.You will mentor engineering teams in adopting AI-enabled engineering practices, automation-first thinking, and continuous improvement.What You BringStrong development expertise in technologies such as Python, Java, TypeScript, or Go.Exp. integrating AI or machine learning capabilities into enterprise applications or digital platforms.Exp. with cloud platforms such as AWS, Azure, or Google Cloud.Understanding APIs, microservices, distributed systems, containerization, and modern integration patterns.Expertise using AI-assisted development tools and engineering productivity accelerators.Expertise with Agile delivery, DevOps practices, CI/CD automation, and engineering lifecycle execution.Having skillsExpertise building and scaling machine learning, generative AI, or intelligent automation solutions in production environments.Familiarity with MLOps, LLM integration, prompt engineering, model monitoring, and AI validation practices.Expertise working within banking, fintech, payments, or other highly regulated industry environments.Relevant certifications in cloud architecture, enterprise solution design, platform engineering, or AI/ML, such as AWS/Azure/GCP Solutions Architect, TOGAF, Certified Kubernetes Administrator, with exposure to Lean Six Sigma considered an advantage.Interested can share your CV at tamnna@ziventra.com or tag someone suitable.
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