Solution Design & Development
Design and develop AI-based solutions under guidance, including:
1. Intelligent Agents/Assistants/Chatbots.
2. Proof-of-concepts (POCs), MVPs, and Pilot solutions for business validation.
3. Integrate AI capabilities into internal tools, applications, or business processes.
4. Automation tools that use AI for ticket handling, workflow assistance, case summarization, and task acceleration.
5. AI-enabled support tools for issue triage, root cause analysis assistance, log analysis, and service productivity improvement.
6. Document and knowledge base search solutions.
7. Develop deployable products using known LLMs to solve functional or technical blockers.
8. AI-enabled productivity tools for internal business users.
Software Development & Sustenance(SDLC Practices)
1. Work within SDLC processes to ensure AI solutions are developed, tested, documented, and released in line with project standards.
2. Support production deployments during sustenance phases by monitoring solution behavior, analyzing issues, and assisting in bug fixes and enhancements.
Business Problem Solving & AI Application
1.Translate business problem statements into AI-driven tools, features, prototypes, or scalable solutions.
2. Work with functional teams to gather requirements, understand workflows, and define AI use cases with measurable outcomes.
3. Support the evaluation of where AI, automation, machine learning, or generative AI can add business value.
Data, Models & Experimentation
1. Work with structured and unstructured data to support AI/ML use cases.
2. Eperiment with modern AI/ML techniques or models(LLMs/SLMs), APIs, and frameworks to solve targeted business problems.
3. Support data preparation, prompt designs, insights generation, model evaluation, and output quality improvement.
4. Participate in model testing, validation, and optimization for business relevance and usability.
Collaboration & Continuous Improvement
1. Collaborate with FES business SMEs, stakeholders, FDC team, developers, analysts, architects to drive solution development.
2. Document use cases, solution logic, technical assumptions, and implementation approach.
3. Stay updated with emerging trends in AI, machine learning, large/small language models, and enterprise AI tools.
4. Monitor deployed AI solutions, analyze logs/issues, and support troubleshooting or improvements.
4. Contribute ideas to expand AI adoption and digital innovation within FES Entities.
