AI/ML Architect

Experience: 10–15 Years

Location: Hyderabad

Work Mode: On-site

Interview Mode: Face-to-Face (F2F)

Role Summary

We are looking for an experienced AI/ML Architect to lead the design, development, and deployment of enterprise-grade AI/ML and Generative AI solutions. The ideal candidate will have strong experience in Machine Learning, Conversational AI, NLP/NLU, LLMs, RAG, AIOps, DevOps/SRE, and enterprise system integration.

The candidate will work closely with business and technical stakeholders to identify AI/ML opportunities, architect scalable solutions, and lead technically complex projects from concept through implementation.

Key Areas of Focus

• Slackbots and Virtual Assistants
• Conversational AI
• Anomaly Detection
• Event Correlation
• AIOps for Infrastructure
• Smart Answers
• NLP/NLU
• LLMs and Generative AI
• Machine Learning and Advanced Analytics

Key Responsibilities

• Lead the end-to-end machine learning project lifecycle, from experimentation and design to deployment and production support.
• Architect and develop virtual assistants using Conversational AI technologies.
• Design and implement AI/ML solutions for enterprise use cases.
• Work with business stakeholders to identify business challenges that can be addressed using AI/ML.
• Lead the development of advanced analytics solutions across different functional areas.
• Design and implement AIOps solutions including clustering, classification, anomaly detection, event correlation, and capacity prediction.
• Leverage LLMs and Generative AI technologies for enterprise applications.
• Provide technical guidance and best practices on LLM and GenAI adoption, particularly for NLP and conversational use cases.
• Design conversational flows, intents, entities, and dialogue experiences.
• Integrate conversational AI and bot systems with backend applications, databases, APIs, and web services.
• Lead complex and technically challenging AI/ML projects from concept to completion.
• Collaborate with DevOps/SRE teams to build reliable and scalable AI/ML solutions.
• Troubleshoot complex issues in distributed enterprise environments.
• Drive innovation and identify opportunities for high-impact AI/ML solutions.
• Mentor and provide technical guidance to engineering and AI/ML teams.

Required Skills

• 10–15 years of experience in AI/ML implementation and enterprise technology environments.
• Strong understanding of supervised and unsupervised learning, deep learning, anomaly detection, and time-series forecasting.
• Strong knowledge of LLMs, Generative AI, NLP, NLU, and Conversational AI.
• Strong programming experience in Python.
• Hands-on experience with Python libraries/frameworks such as Pandas, NumPy, TensorFlow or equivalent.
• Minimum 5 years of experience in designing, developing, and deploying conversational bots/virtual assistants.
• Strong experience in AIOps use cases such as:
• Anomaly Detection
• Clustering
• Classification
• Event Correlation
• Capacity Prediction
• Experience with Observability/Monitoring tools such as Prometheus, Splunk, Datadog, and Grafana.
• Strong DevOps/SRE experience, preferably 5–7 years.
• Experience integrating AI/bot solutions with backend systems, databases, APIs, and web services.
• Strong troubleshooting and analytical skills in complex distributed environments.
• Excellent communication, presentation, stakeholder management, and collaboration skills.
• Ability to work independently and take ownership of complex technical initiatives.

Generative AI / LLM Skills

• LLM application development
• RAG architecture and implementation
• Prompt engineering
• LLM evaluation
• Hallucination reduction
• AI safety and guardrails
• LLM deployment and scaling
• Knowledge of fine-tuning techniques such as LoRA/adapters is desirable
• Experience with AI agents/Agentic AI is desirable
• Understanding of vector databases and semantic/hybrid search is desirable

Preferred Qualifications

• Experience building enterprise-grade Conversational AI platforms.
• Experience with RAG-based applications and LLM-powered assistants.
• Experience with AIOps/IT Operations analytics.
• Experience with observability platforms and infrastructure monitoring.
• Experience with cloud platforms and production AI/ML deployments.
• Experience with MLOps and model monitoring.
• Experience working in complex, distributed enterprise environments.

Soft Skills

• Strong problem-solving and analytical abilities.
• Excellent verbal and written communication.
• Strong stakeholder management skills.
• Ability to lead technical discussions and architecture decisions.
• Self-motivated and capable of working independently.
• Strong leadership and mentoring capabilities.

Skills: design,nlp,ai,anomaly detection,ml