AI Backend Engineer

Deutsche Telekom Digital Labs • Python • 1 month ago
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≈ $27k – $111k per year (Estimated)
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In office (Gurgaon)
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Deutsche Telekom Digital Labs

DTDL (Digital Transformation and Data Analytics Solutions) is an Indian technology firm specializing in digital solutions, data management, and enterprise IT services. The company provides customized software development, cloud integration, and advanced analytics to help businesses optimize their operations and scale efficiently. Based in India, it serves as a digital transformation partner for organizations looking to leverage technology for business growth and modernization.
dtdl.in • HQ: Gurgaon, India • Information Technology • Telecommunications • Mobile Networks • 1001-5000 employees • Est. 2018

We are looking for a highly skilled AI Backend Engineer with hands-on experience in building next-generation AI applications using agentic AI, generative AI, conversational AI, and voice AI technologies.

Responsibilities:

  • Design and develop scalable AI backend systems and intelligent agents.
  • Build multi-agent workflows using LangGraph and LangChain.
  • Develop voice and conversational AI applications integrated with LLMs.
  • Implement RAG pipelines and AI orchestration frameworks.
  • Optimise AI model interactions, latency, and backend performance.
  • Collaborate with product and engineering teams to deliver AI-driven solutions.

Requirements:

  • Key Skills Required: Agentic AI Development, Generative AI Applications, Conversational AI and Voice Bots, LLM Integration and Fine-Tuning, LangChain and LangGraph, RAG (Retrieval-Augmented Generation), AI Workflow Orchestration, Python and FastAPI/Flask, Vector Databases (Pinecone, Weaviate, ChromaDB and FAISS), Prompt Engineering, OpenAI/Claude/Gemini APIs, REST APIs and Backend Architecture, and Cloud Platforms (AWS/GCP/Azure).

Preferred Qualifications:

  • Experience with autonomous AI agents and multi-agent systems.
  • Knowledge of speech-to-text and text-to-speech technologies.
  • Familiarity with AI observability, evaluation, and monitoring tools.
  • Strong understanding of backend system design and microservices.
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