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EXL

Agentic AI – Prompt Engineer

EXL

. Design, optimize, and deploy prompt-driven solutions for LLM-powered applications .

Posted 10/14/2026full-timeNoida • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and deploying LLM-powered applications, with strong proficiency in Python and TypeScript for automation, data processing, and application development. Capable of integrating AI capabilities into front-end applications using frameworks like React and familiar with cloud platforms and microservices architecture.

Highest-signal resume keywords
Python ProficiencyTypeScript ProficiencyLLM ExperienceNLP UnderstandingCloud Platform Experience

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
PythonTypeScriptLLM WorkflowsPrompt EngineeringModel EvaluationNLP ConceptsData ProcessingAPI IntegrationsReactMicroservices
Soft Skills
Analytical SkillsDebugging SkillsProblem-Solving Skills
Tools & Technologies
LangChainLlamaIndexAzureAWSGCP
Industry Keywords
AIMLNLPGenAIREST APIsDeployment Workflows

Tech Stack

Tools & technologies
AWSAzureCloudGoogle Cloud PlatformMicroservicesPythonReactTypeScript

About the role

Key responsibilities & impact
  • Design, optimize, and deploy prompt-driven solutions for LLM-powered applications
  • Collaborate closely with AI, product, and engineering teams
  • Build scalable and high-impact GenAI features
  • Integrate LLM workflows into front-end applications

Requirements

What you’ll need
  • 4 years of experience in AI/ML, NLP, software engineering, or related domains
  • Strong hands-on experience in Python and TypeScript
  • Proficiency in Python for automation, scripting, data processing, and API integrations
  • Proficiency in TypeScript for backend logic, APIs, and application development
  • Practical experience working with LLMs, prompt engineering, and model evaluation
  • Understanding of NLP concepts, embeddings, and vector search pipelines
  • Strong analytical, debugging, and problem-solving skills
  • Experience with React for integrating AI capabilities into front-end applications (added advantage)
  • Familiarity with LangChain, LlamaIndex, or other LLM orchestration frameworks
  • Experience with cloud platforms (Azure, AWS, GCP)
  • Knowledge of microservices, REST APIs, and deployment workflows