Agent Engineer

Join Zafin, a leading provider of banking software solutions. As an Agent Engineer, you will design, build, integrate, test, deploy, and continuously improve AI agents and supporting software capabilities within client banking environments. You will work within a cross-functional AIOS squad and follow the AIOS delivery lifecycle. This role offers opportunities for growth and technical leadership.

• Design, build, integrate, test, deploy, and continuously improve AI agents, workflows, prompts, tools, and supporting software capabilities.
• Collaborate with cross-functional teams to ensure AI agents reflect intended business logic, integrate effectively within enterprise systems, and meet quality standards.
• Execute the full AIOS delivery lifecycle on assigned initiatives, from Analysis & Concept to Immediate Development, Reliability Testing, and Assisted Deployment.
• Understanding of large language model fundamentals, prompt design, tool use, and common approaches for building AI-powered applications
• Understanding of privacy, security, data governance, and responsible AI practices applicable to enterprise AI systems, particularly with regulated industries
• Degree in Comp Sci, Comp Eng, Engineering, or other technical field, or equivalent or practical experience
• Strong analytical and debugging skills
• Typically, 1–10+ years of experience in software or AI engineering, automation, data engineering, or related technical roles, with levels determined by demonstrated scope, technical depth, independence, and leadership capability
• Proficiency in at least one relevant programming language, such as Python, TypeScript, or Java
• Experience or demonstrated ability building software applications, automation workflows, data-enabled systems, or AI solutions
• Familiarity with cloud-native applications, CI/CD, monitoring, logging, observability, and production-support practices
• Familiarity with integrating APIs, enterprise applications, databases, and structured and unstructured data sources
• Understanding of testing and evaluation practices for AI-driven systems, including behavioural, reliability, and safety evaluation
• Ability to interpret technical designs and translate them into maintainable working implementations
• Familiarity with AI engineering and delivery metrics (pull request acceptance rate, autonomous merge rate, cost per accepted change) as core measures of engineering quality
• Understanding of software engineering fundamentals, including source control, testing, debugging, code review, APIs, data structures, and deployment practices
• Experience building internal AI tools or platforms adopted by other engineering teams
• Domain knowledge of banking, financial services, or large-scale enterprise IT environments