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The Digital S/W Engineer Sr Mgr accomplishes results through the management of professional team(s) and department(s). Responsible for Design and implementation of cutting-edge AI/ML solutions that power intelligent, multilingual digital experiences across customer-facing and operational platforms. Requires broad full-stack engineering expertise with deep specialization in AI/ML with an ability to build and optimize LLM-powered workflows, agentic AI systems, and machine learning models to enable natural language understanding, intelligent automation, and personalized self-service, bridging intelligent systems with enterprise-grade digital platforms across millions of interactions spanning multiple languages. Full management responsibility of a team, which may include management of people, budget and planning and duties such as performance Evaluation.
Job Responsibility:
Lead the design and development of scalable, enterprise-grade conversational AI and agentic systems for real-time customer interaction use cases
Build and optimize AI/ML solutions including LLM-powered workflows
Develop and implement RAG pipelines and knowledge-based AI integrations
Design and deploy multi-agent systems for complex business use cases
Apply prompt engineering and optimize LLM performance, cost, and accuracy
Build intelligent automation solutions for customer journeys and digital workflows
Integrate AI capabilities into existing enterprise platforms and architectures
Collaborate with cross-functional teams to deliver end-to-end solutions
Ensure system scalability, reliability, and performance in production environments
Drive best practices in architecture, coding standards, and AI implementation
Requirements:
11–16 years of experience in application development or enterprise engineering roles
Strong hands-on expertise in Java, Microservices, and REST APIs
Expert-level proficiency in Python (mandatory)
2+ years of hands-on experience with AI/ML, LLMs (e.g., GPT, Claude, Gemini)
Experience with RAG, prompt engineering, and vector databases
Familiarity with agentic AI frameworks (e.g., LangChain, LangGraph, CrewAI)
Full-stack development experience with modern frontend frameworks (e.g., React.js/Angular)
Strong understanding of system design, distributed systems, and cloud platforms
Experience with SQL/NoSQL databases and real-time data processing
Exposure to MLOps practices including deployment, monitoring, and lifecycle management
Nice to have:
Experience in Financial Services / Banking domain
Exposure to recommendation systems, personalization, or conversational AI
Knowledge of customer journey analytics, sentiment analysis, or automation workflows
Experience working in product-based or large-scale enterprise environments