Artificial Intelligence Engineer

Department Icon Data Science Analytics & Machine Learning
Posted: 2 days ago
3-8 years
Hybrid - Bengaluru
Data Science Analytics & Machine Learning
work from office
Full Time
Closes 9 Jan 2027

Posted: 2 days ago
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Job Description
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Job Description

Experience : 3 to 8

Notice : Immediate to 15 days Max

Location Bangalore

AI Engineer- We are seeking a AI Engineer to build and deliver production-grade agentic AI systems for enterprise use. The engineer will develop multi-agent workflows, integrate large language models into existing enterprise systems, and support the deployment and automation needed to run them reliably and securely in production.

This is a hands-on engineering engagement. The work centers on building agents, orchestration logic, and supporting infrastructure that performs under real production workloads, not on proof-of-concept or advisory work.

Scope of Work

  • Build AI agents and multi-agent systems using frameworks with LangGraph and LangChain tools.
  • Develop and tune prompt engineering workflows across multiple LLMs (GPT, Claude, LLaMA), balancing reliability, cost, and latency.
  • Develop REST APIs, WebSocket services, and event-driven pipelines for real-time AI services that remain stable under load.
  • Automate testing and releases through Jenkins CI/CD, and maintain code and documentation standards using Git, Jira, and Confluence.
  • Deployment of AI Application in enterprise adhering to best practices
  • Use AI-augmented development tools such as Claude Code and Codex to accelerate delivery.
  • Coordinate with platform, security, and product teams to deliver scalable, secure deployments.

Must-Have Skills

  • 4-6 years in Machine Learning, AI, or a related field, with production systems delivered.
  • At least 1 year building custom Agentic AI applications
  • Strong Python skills and sound modern development practices.
  • Hands-on experience with LLMs and prompt engineering across the full application lifecycle.
  • Demonstrated experience building AI agents with LangGraph.
  • Familiarity with at least one enterprise cloud AI platform for building and deploying agentic applications, such as Azure AI Foundry, AWS Bedrock, or Google Gemini Enterprise, including cloud-native deployment practices.
  • Working knowledge of REST APIs, WebSockets, and event-driven systems.
  • Proficiency with CI/CD tooling (Jenkins) and version control (Git).
  • Fluency with AI-augmented development tools for rapid prototyping.
  • Strong written and verbal communication, an analytical approach to problem-solving, and the ability to work independently within a cross-functional team.
  • Data layer curations and integration with source system for agentic application

Good-to-Have Skills

  • Familiarity with Databricks.
  • Exposure to MLOps/LLMOps workflows and application monitoring.
  • Knowledge of enterprise security, compliance, and governance for AI systems.
  • Familiarity with code and model lifecycle management practices.

Skills

Deep LearningProcessingMachinePythonNatural Language ProcessingArtificial IntelligenceProcessMachine LearningPythonMachine LearningPrompt EngineeringLarge Language ModelsAi EngineerAiLlmsGptLangchainLanggraphAi AgentsAgenticAgentic AiMulti-agent SystemsMlopsLlmopsAws BedrockDatabricksArtificial Intelligence

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