Key Responsibility Area: o Lead and manage a team of software developers, Testers and automation engineers. o Define project goals, scope, and deliverables; ensure successful execution. o Provide technical guidance and mentorship. o Identify opportunities for process improvement and automation. o Implement best practices and tools for efficient development. o Drive innovation and continuous improvement in methodologies. o Collaborate with product, QA, and operations teams to define requirements. o Maintain strong stakeholder relationships aligning technology with business goals. o Define and track KPIs for project success. o Monitor team performance and provide feedback. o Experience in banking applications and CRM processes. o Continuously update rules/procedures and manage daily activities. o Support special projects. Eligibility Criteria: Must have: o Strong technical background, expertise in two or more languages (.Net, C#, JavaScript, Java, PHP, GO). o CRM project experience (SugarCRM or Salesforce for Banks/Credit Unions). o Proven delivery of complex applications and CRM projects. o Experience in automation strategies for efficiency. o Knowledge of Generative AI, Agentic architectures, prompt engineering, RAG pipelines. o LLM-based product development (fine-tuning, embeddings, vector DBs, inference optimization). o Familiarity with AI platform architecture (local/cloud). o Agile/Scrum and DevOps knowledge preferred. o Excellent leadership, communication, and self-learning skills. o Ability to manage 15+ developers. Nice to have: o Familiarity with no code Low code platforms, Xamarin/Maui, API integrations. o Cloud computing (AWS, Azure, GCP, Oracle CP). o Exposure to AI-driven automation, cloud AI services, and open-source LLM frameworks. o Knowledge of model evaluation, monitoring, and ethical AI practices. o Experience with API integrations in complex banking applications environment. o Exposure to AI-driven automation strategies for software development processes. o Knowledge of model evaluation and monitoring for production AI systems. o Understanding of ethical AI practices and compliance in financial technology environments.