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

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Slackbots and Virtual Assistants

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Conversational AI

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Anomaly Detection

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Event Correlation

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AIOps for Infrastructure

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Smart Answers

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NLP/NLU

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LLMs and Generative AI

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Machine Learning and Advanced Analytics

Key Responsibilities

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Lead the end-to-end machine learning project lifecycle, from experimentation and design to deployment and production support.

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Architect and develop virtual assistants using Conversational AI technologies.

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Design and implement AI/ML solutions for enterprise use cases.

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Work with business stakeholders to identify business challenges that can be addressed using AI/ML.

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Lead the development of advanced analytics solutions across different functional areas.

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Design and implement AIOps solutions including clustering, classification, anomaly detection, event correlation, and capacity prediction.

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Leverage LLMs and Generative AI technologies for enterprise applications.

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Provide technical guidance and best practices on LLM and GenAI adoption, particularly for NLP and conversational use cases.

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Design conversational flows, intents, entities,



and dialogue experiences.

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Integrate conversational AI and bot systems with backend applications, databases, APIs, and web services.

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Lead complex and technically challenging AI/ML projects from concept to completion.

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Collaborate with DevOps/SRE teams to build reliable and scalable AI/ML solutions.

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Troubleshoot complex issues in distributed enterprise environments.

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Drive innovation and identify opportunities for high-impact AI/ML solutions.

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Mentor and provide technical guidance to engineering and AI/ML teams.

Required Skills

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10–15 years of experience in AI/ML implementation and enterprise technology environments.

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Strong understanding of supervised and unsupervised learning, deep learning, anomaly detection, and time-series forecasting.

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Robust knowledge of LLMs, Generative AI, NLP, NLU, and Conversational AI.

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Strong programming experience in Python.

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Hands-on experience with Python libraries/frameworks such as Pandas, NumPy, TensorFlow or equivalent.

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Minimum 5 years of experience in designing, developing, and deploying conversational bots/virtual assistants.

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Strong experience in AIOps use cases such as:

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Anomaly Detection

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Clustering

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Classification

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Event Correlation

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Capacity Prediction

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Experience with Observability/Monitoring tools such as Prometheus, Splunk, Datadog, and Grafana.

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Strong DevOps/SRE experience, preferably 5–7 years.

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Experience integrating AI/bot solutions with backend systems, databases, APIs, and web services.

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Strong troubleshooting and analytical skills in complex distributed environments.

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Excellent communication, presentation, stakeholder management, and collaboration skills.

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Ability to work independently and take ownership of complex technical initiatives.

Generative AI / LLM Skills

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LLM application development

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RAG architecture and implementation

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Prompt engineering

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LLM evaluation

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Hallucination reduction

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AI safety and guardrails

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LLM deployment and scaling

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Knowledge of fine-tuning techniques such as LoRA/adapters is desirable

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Experience with AI agents/Agentic AI is desirable

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Understanding of vector databases and semantic/hybrid search is desirable

Preferred Qualifications

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Experience building enterprise-grade Conversational AI platforms.

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Experience with RAG-based applications and LLM-powered assistants.

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Experience with AIOps/IT Operations analytics.

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Experience with observability platforms and infrastructure monitoring.

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Experience with cloud platforms and production AI/ML deployments.

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Experience with MLOps and model monitoring.

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Experience working in complex, distributed enterprise environments.

Soft Skills

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Strong problem-solving and analytical abilities.

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Excellent verbal and written communication.

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Strong stakeholder management skills.

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Ability to lead technical discussions and architecture decisions.

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Self-motivated and capable of working independently.

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Strong leadership and mentoring capabilities.

📌 AI/ML Architect (Madhavaram)
🏢 Recognized
📍 Madhavaram