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Lead Applied AI Engineer - Azure - Manager

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Hybrid

Lead Applied AI Engineer - Azure - Manager

Anlage Infotech

Lead Applied AI Engineer - Azure - Manager

Skills

Google Cloud PlatformSQL QueriesReactNodePythonData ScienceJavaDevOpsC#PyTorchTensorFlowMachine LearningAIAWSGitHubAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Bagalur, Karnataka 562122, India

Work mode:

Hybrid

Published on:

24 August 2026

What they need


Skill - Lead Applied AI Engineer - Dotnet Fullstack +Azure Services (No Devops) + AI

Level - Manager

Experience - 10-13 Yrs

Work location - Hyderabad/Bangalore

Interview Mode - Virtual

Interview Date - 7-Aug-26, 8-Aug-26, 14-Aug-26, 14-Aug-26, 21-Aug-26, 22-Aug-26, 24-Aug-26

Primary Skills - (.Net/C#)+(Angular/React)+(Azure Services)+ (AI/ML / Generative AI / GenAI / LLMs / Agents / Assistants) + (Team Management)

The successful candidate will possess:

  • Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.

Required Qualifications:

  • A bachelors degree in computer science, software engineering, data science, machine learning, or related discipline. Experience is the most relevant factor.

  • 5+ years of experience with most of the following: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, as well as unit testing frameworks.

  • 3+ years of experience building AI/ML and agentic applications, with hands-on GenAI experience across LLM integration (OpenAI, Anthropic, or open-source models), RAG pipelines, prompt engineering, vector databases, evaluations, and AI agent orchestration.

  • 3+ years of experience with cloud-native engineering, using FaaS, PaaS, or micro-services on any of the cloud hyperscalers such as Azure, AWS, or GCP, including their AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI, plus application-level infrastructure-as-code and cost-aware engineering (FinOps accountability).

  • Prior software engineering experience with the understanding of Business Context Diagrams (BCD), sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and code instrumentations, and AI-augmented spec-driven development.

  • Prior experience using methodologies & tools such as XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (e.g. LangFuse, LangSmith, or equivalent multi-agent orchestration tools) etc. to deliver high-quality products rapidly.

Other:

* Ability to travel 10%, on average, based on the work you do and products you build.

* Limited immigration sponsorship may be available

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