Power Apps Developer - Power Automate

(a) Title: L2 / L3 Engineer AI, AIOps & Intelligent Automation (LLM / Chatbot Engineering)

(b)Business/Function: Cloud Engineering & Infrastructure Services

(c) Level: L2/L3

(d) Location: Mumbai

(f) Summary: The L2 / L3 Engineer – AI, AIOps & Intelligent Automation will be responsible for designing, developing, and implementing AI-driven solutions, including chatbots, Large Language Model (LLM)-based systems, and AIOps frameworks using open-source and enterprise technologies. The role focuses on enhancing IT Service Delivery, Observability, Command Center operations, and automation using AI/ML techniques, with an emphasis on proactive monitoring, anomaly detection, incident automation, and intelligent user interactions.

Additional Information

(a) Responsibilities:Design and develop AI/ML-based solutions for IT operations and business automation

(b) Build and deploy chatbots using LLMs, NLP frameworks, and conversational AI platforms (e.g., Dialogflow, Azure OpenAI, LangChain, Rasa)

(c) Develop and integrate GenAI/LLM-based applications for:

(d) ITSM automation

(e) Knowledge management

(f) Incident troubleshooting

(g) User query resolution

AIOps & Observability

• Implement AIOps use cases such as:
• Anomaly detection in system metrics
• Alert correlation and noise reduction
• Root cause analysis (RCA)
• Predictive failure analysis
• Integrate AI solutions with:

Prometheus, Grafana, ELK stack

• Monitoring tools and observability platforms

Automation & Integration

• Develop automation pipelines integrating:

AI models

• Power Automate / Python scripts
• APIs and microservices

Build intelligent workflows combining:

• Alerts AI processing Task/incident generation

L2 Responsibilities:

• Monitor AI models and chatbot performance
• Handle basic tuning and troubleshooting
• Resolve chatbot errors and data issues
• Support deployment and testing of AI solutions

L3 Responsibilities:

• Design and implement LLM-based architectures (RAG, embeddings, vector DBs)
• Optimize AI models for performance, accuracy, and scalability
• Build intelligent agents and decision-making systems (Agentic AI)
• Integrate AI solutions with enterprise systems and observability platforms
• Handle model lifecycle management and advanced debugging

Governance & Security

• Ensure data privacy, security, and compliance in AI solutions
• Maintain proper access control for models and APIs
• Document AI workflows, models, and system architecture

Collaboration

Work with:

• IT Service Delivery teams
• Observability / Command Center
• Business stakeholders
• Identify opportunities to introduce AI-driven automation

Requirements

(a) Education: Bachelor’s degree in Computer Science / IT / Engineering or equivalent

Master’s degree in AI/ML/Data Science is preferred

(b) Experience: L2: 2–4 years in AI/ML / automation / chatbot development

L3: 4–8+ years in AI/ML, LLM, AIOps, or intelligent automation

(c) Certifications:

• Microsoft Azure AI / AI Engineer Certification – Preferred
• Google Professional ML Engineer – Preferred
• Certifications in Data Science / NLP / AI – Added advantage
• Python / ML certifications (Coursera, AWS, etc.) – Good to have

(d) Knowledge: Strong understanding of:

• AI/ML concepts (supervised/unsupervised learning)
• Natural Language Processing (NLP)
• LLM frameworks (GPT, OpenAI, Gemini, etc.)
• Knowledge of:
• RAG (Retrieval-Augmented Generation)
• Embeddings and Vector Databases (FAISS, Pinecone, Chroma)
• AIOps concepts:
• Anomaly detection
• Alert correlation
• Predictive monitoring
• Familiarity with:
• Observability tools (Prometheus, Grafana, ELK)
• APIs and microservices

(e) Skills:

• Strong programming skills in:
• Python (mandatory)
• REST API integration

Core Technical Skills

Experience with:

• LLM frameworks (LangChain, LlamaIndex)
• Chatbot development (Dialogflow, Rasa, Bot Framework)
• Open-source AI tools and libraries

Ability to build:

• Chatbots
• AI agents
• Knowledge assistants
• Automation pipelines using AI

Advanced Skills (L3 Preferred)

• Designing RAG-based architectures

Working with:

• Vector databases
• Prompt engineering
• Fine-tuning models

Experience with:

• Docker / containerization
• Cloud platforms (Azure, GCP)
• Integration of AI with ITSM and monitoring systems

Soft Skills

• Strong analytical and problem-solving skills
• Ability to translate business problems into AI solutions
• Excellent communication and stakeholder interaction
• Ability to work in high-pressure command center environments