Senior AI Developer / Engineer

About the Role

Qentelli is hiring a Senior AI Developer / Engineer in Hyderabad to build intelligent capabilities for an enterprise integration and analytics platform. The position is centered on agentic AI, predictive analytics, smart extraction of information from emails and documents, and AI-driven insights across contract, resource, and transition management data. The solution stack includes Azure, Spring Boot, React, and modern AI/ML tools.

What You’ll Work On

You will shape AI/ML solutions that automate recommendations and decision-making, develop AI agents that analyze operational metrics, and create models that forecast outcomes such as transition success, onboarding timelines, and engagement performance. The role also involves building NLP systems for document and email understanding, as well as integrating these features into existing platform services.

Key Responsibilities

• Design AI/ML architectures for agentic features that can automate recommendations and decisions.
• Create intelligent agents to evaluate transition KPIs, resource utilization, and contract performance.
• Build recommendation systems for resource allocation, learning suggestions, and risk detection.
• Develop predictive models for transition outcomes, onboarding timelines, and engagement results.
• Design NLP solutions for document analysis and extracting data from emails.
• Define end-to-end ML workflows for training, validation, deployment, and monitoring.
• Develop autonomous AI components that can analyze information, identify patterns, and recommend actions.
• Implement conversational AI for querying KPIs, metrics, and engagement information.
• Create anomaly detection models for RAID logs, financial deviations, and KPI changes.
• Build sentiment analysis models for CSAT feedback and review comments.
• Develop document intelligence features for contracts, SOWs, and transition documents.
• Set up intelligent classification and tagging for contracts, resources, and transition assets.
• Design NLP-based systems to extract and classify inbound email content.
• Build parsing logic that converts unstructured emails into structured records.
• Develop named entity recognition models to identify contracts, resources, dates, and metrics.
• Create automated email and document routing systems.
• Implement summarization for long transition plans and review documents.
• Build ML models for engagement success, resource performance, and transition risk prediction.
• Develop time-series forecasting models for KPI trends and financial projections.
• Create clustering and classification models for skill matching and contract grouping.
• Implement recommendation algorithms for resource allocation and personalized learning paths.
• Add explainability features that make model outputs and recommendations transparent.
• Integrate AI/ML services with Java Spring Boot backend systems through REST APIs.
• Develop Python microservices for AI workloads and deploy them on Azure Kubernetes Service.
• Build real-time inference endpoints for application use cases.
• Create batch scoring pipelines for large-volume data processing.
• Design feedback mechanisms that improve model performance over time.
• Use Azure AI offerings such as Azure OpenAI, Cognitive Services, and Azure Machine Learning.
• Integrate Azure OpenAI for LLM-based and generative AI functionality.
• Build MLOps pipelines for versioning, deployment, and monitoring using Azure ML.
• Configure model endpoints, A/B testing, and canary releases.
• Set up monitoring, drift detection, and retraining workflows.
• Improve AI service performance and cost efficiency on Azure.
• Perform exploratory analysis on integrated contract, resource, and transition data.
• Carry out feature engineering and selection to improve model quality.
• Run experiments, tune hyperparameters, and evaluate model performance.
• Partner with data engineers on ML-ready data pipeline design.
• Document model design, training approach, and performance metrics.
• Guide development teams on AI/ML best practices.
• Review AI code and model implementations.
• Define testing approaches for model validation and performance assessment.
• Stay updated on AI/ML trends, Azure services, and emerging technologies.
• Prepare technical documentation for AI features and model behavior.

Experience and Skills Required

• At least 4 years of hands-on experience in AI/ML development and deployment.
• Strong understanding of supervised, unsupervised, and reinforcement learning.
• Deep NLP experience, including text classification, NER, sentiment analysis, and document understanding.
• Practical exposure to agentic AI systems or autonomous agents.
• Knowledge of large language models and generative AI use cases.
• Experience with predictive analytics, forecasting, and recommendation engines.
• Familiarity with deep learning architectures such as transformers, RNNs, and CNNs.
• Advanced Python skills along with ML libraries such as scikit-learn, TensorFlow, PyTorch, and Hugging Face Transformers.
• Strong working knowledge of Azure AI services, including Azure OpenAI, Cognitive Services, and Azure Machine Learning.
• Experience exposing ML models through REST APIs and microservices.
• Understanding of MLOps practices such as versioning, CI/CD, monitoring, and retraining.
• Good command of data handling tools such as Pandas, NumPy, and Polars.
• Hands-on experience with Docker and Kubernetes/AKS deployment.
• Working knowledge of Java Spring Boot for backend integration is preferred.
• Knowledge of vector databases and embedding-based retrieval is preferred.
• Strong Azure Machine Learning platform experience.
• Hands-on exposure to Azure OpenAI and prompt engineering.
• Familiarity with Azure Cognitive Services such as Text Analytics, Form Recognizer, and Document Intelligence.
• Experience with Azure Functions for serverless AI processing.
• Understanding of Azure storage and data services such as Blob Storage, Data Lake, and Cosmos DB.
• Exposure to Azure DevOps for ML pipeline orchestration.
• Strong SQL skills for extraction and feature engineering, with MySQL preferred.
• Experience working with MongoDB or other NoSQL systems for unstructured data.

Eligibility

Any graduate can apply for this role.

Location

This is a Hyderabad, India based onsite position.

Company Overview

Qentelli is a global technology partner focused on business innovation, supported by an experienced team, best-practice delivery, and specialized tools. Its work centers on strengthening operations through SAP-oriented environments with smooth integration and measurable business value.

Additional Information

No stipend, salary range, opening count, start date, or duration was specified in the source. No perks or benefits were listed.