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Senior Artificial Intelligence Developer

Senior Artificial Intelligence Developer

BegigIndia
30+ days ago
Job description

Job Role : Senior AI Developer.

Job Type : Full-Time.

Work Mode : Remote.

Were seeking a Senior AI Developer with a strong background in building and deploying AI / ML-powered applications in production environments.

This role is ideal for someone passionate about working with Large Language Models, Conversational AI, Agentic AI, and cutting-edge AI infrastructure.

Core Requirements :

  • 5+ years of software development experience, with 2- 3 years in AI / ML applications.
  • Expert-level Python skills and deep knowledge of the AI / data science ecosystem.
  • LLM expertise : Prompt engineering, RAG pipelines, and model fine-tuning.
  • Agentic AI : Designing multi-step autonomous agents capable of reasoning, tool use, and adaptive decision-making.
  • Conversational AI : NLU, dialogue management, and integration with STT / TTS APIs (e.g., OpenAI, Azure Speech, ElevenLabs).
  • Solid grasp of system design, API architecture, and building scalable, low-latency systems.

Preferred Skills :

  • Hands-on experience with LangChain or LangGraph for complex agent workflows.
  • Experience with orchestration frameworks for autonomous agents and multi-agent collaboration.
  • Familiarity with cloud infrastructure (AWS), Docker / Kubernetes, and CI / CD.
  • Experience with vector databases (Pinecone, Qdrant, Milvus, etc.)
  • Bonus : Basic frontend development (React / Vue) and real-time voice streaming or STT model deployment (e.g., Whisper).
  • Key Responsibilities :

  • Design, build, and deploy autonomous AI agents capable of reasoning, planning, and executing multi-step tasks.
  • Integrate Agentic AI workflows into production systems to automate complex processes and enhance decision-making.
  • Implement tool-using agents that interact with APIs, databases, and external services in real time.
  • Develop multi-agent collaboration systems for distributed problem-solving and task delegation.
  • Build adaptive learning systems where agents improve performance based on feedback and historical data.
  • Collaborate with product teams to identify business problems that can be solved using Agentic AI and LLM-based solutions.
  • Optimize AI pipelines for performance, cost efficiency, and scalability.
  • (ref : hirist.tech)

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