Manager - Business Support- Happy Robot

Job Title: Manager – Happy Robot 

Job Location: Chennai 

 

This role is responsible for configuring, deploying, operating, and continuously improving AI-powered automation solutions on the HappyRobots platform. This role focuses on low-code / no-code GenAI product configuration and ensures AI solutions are production-ready, compliant, scalable, cost-optimized, and ethically sound. The position serves as a critical execution layer between Business Unit IT (BUIT) priorities and real-world AI deployments, enabling reliable and responsible AI automation across digital and voice channels. 

 

Key Responsibilities: 

1. GenAI Product Configuration & Deployment

• Configure and deploy low-code/no-code GenAI-powered conversational and automation solutions on the HappyRobots platform. 

• Implement workflows, business rules, orchestration logic, and integrations based on BUIT-defined priorities and solution designs. 

• Perform prompt engineering, policy engineering, and guardrail configuration for LLM-powered agents. 

• Configure multi-channel AI experiences across voice, email, SMS, and chat. 

 

1. Data Preparation, Annotation & Model Enablement

• Perform data annotation, labeling, cleansing, and validation for structured and unstructured datasets. 

• Design and generate synthetic data when real data is insufficient or unavailable. 

• Support training, fine-tuning, testing, and evaluation of AI models (including LLM-based workflows). 

• Ensure data quality, lineage, and traceability across training and inference pipelines. 

 

1. Testing, Validation & Responsible AI

• Conduct functional, performance, and regression testing of configured AI solutions. 

• Prepare audit logs, model cards, decision records, and test documentation. 

• Evaluate AI solutions for:  

• Bias and fairness 

• Ethical compliance 

• Explainability and transparency 

• Ensure adherence to Responsible AI, data privacy, and regulatory standards. 

 

1. Production Support & Continuous Improvement

• Monitor AI solutions in production for:  

• Accuracy and response quality 

• Latency, availability, and throughput 

• Cost and token usage optimization 

• Perform issue analysis, root cause identification, and corrective actions. 

• Implement continuous improvements through prompt refinement, workflow optimization, and configuration updates. 

 

1. MLOps & Platform Operations

• Support model lifecycle management, including versioning, upgrades, rollback strategies, and registry management. 

• Assist with platform and model upgrades while ensuring solution stability. 

• Collaborate on deployment pipelines, monitoring dashboards, and alerting mechanisms. 

• Support scaling, reliability, and resilience of AI solutions. 

 

1. Integration & Backend Enablement

• Configure and manage API integrations with internal systems and third-party platforms. 

• Support data flows across conversational agents, databases, and enterprise systems. 

• Work with backend services for authentication, security, and system interoperability. 

 

1. Operational & Automation Use-Case Enablement

• Enable AI Workers and automation use cases such as:  

• Appointment scheduling 

• Vendor coordination 

• Shipment tracking 

• Document ingestion and data entry 

• Configure contextual understanding in TTS and voice-based AI, including tone, rhythm, and intent fidelity. 

• Support document processing workflows, including extraction, validation, and system handoffs. 

 

Required Qualification & Skills: 

• Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field.  

• Minimum 3 years of relevant experience in the GenAI domain 

• Proficiency in Python (mandatory) for AI workflows, automation, and data processing. 

• Full-stack experience with React, TypeScript, and Node.js. 

• Strong understanding of APIs, backend services, and system integrations. 

• Hands-on experience building and operating AI-powered applications. 

• Practical expertise in:  

• Large Language Model (LLM) prompting and tuning 

• Prompt orchestration and policy engineering 

• Understanding of ML/DL fundamentals 

• Experience working with conversational AI, NLP, and GenAI platforms. 

• Experience with data pipelines, preprocessing, and dataset management. 

• Exposure to MLOps practices, including:  

• Model deployment 

• Monitoring and evaluation 

• Scaling and cost optimization 

• Familiarity with model/version registries and lifecycle management. 

• Working knowledge of database design and processing (SQL/NoSQL). 

• Understanding of data modeling for conversational and automation workloads. 

• Advanced analytical and reasoning abilities to interpret AI behavior and outcomes. 

• Experience configuring multi-channel conversational systems (voice and digital). 

• Strong grasp of workflow coordination and automation logic. 

• Understanding of context-aware TTS systems and voice AI design considerations. 

• Hands-on experience with document processing and intelligent data entry workflows. 

• Experience with low-code / no-code AI platforms or enterprise automation tools. 

• Familiarity with Responsible AI frameworks, model governance, and compliance controls. 

• Exposure to cloud environments (Azure, AWS, or GCP) in AI deployments. 

• Understanding of cost controls and token management for LLM-based systems. 

• Comfort working in cross-functional teams (Product, BUIT, Compliance, Ops). 

• Strong documentation and operational handover skills.