Artificial Intelligence Engineer - Gurugram - TheHireHub

    TheHireHub
    TheHireHub Gurugram

    2 days ago

    ₹900,000 - ₹2,200,000 (INR) per year *
    Description

    Company Overview

    is a recruiter-first AI hiring platform built by recruitment professionals with over 20+ years of industry experience. Designed to automate and elevate the entire hiring lifecycle, the platform leverages a multi-agent AI architecture to manage job creation, sourcing, outreach, screening, evaluation, interview scheduling, and analytics. combines applied AI, workflow automation, and human-in-the-loop intelligence to help organizations hire faster, smarter, and with higher precision.

    Role Overview

    We are seeking a Senior AI Engineer to design, build, and scale the AI systems that power 's multi-agent recruiting platform. This role focuses on architecting intelligent workflows using large language models (LLMs), retrieval systems, and agent orchestration frameworks to deliver production-grade AI capabilities across hiring use cases.

    You will be responsible for building end-to-end AI pipelines that enable autonomous and semi-autonomous agents to reason, evaluate candidates, generate outreach, manage screening, and support decision-making—while ensuring performance, cost efficiency, and reliability at scale.

    Key Responsibilities

    • Architect and implement LLM-driven multi-agent systems for recruitment workflows including job analysis, candidate matching, outreach, screening, and evaluation.
    • Design and maintain modular AI pipelines combining retrieval, reasoning, scoring, and response generation layers.
    • Build and orchestrate agent workflows using frameworks such as LangChain, LangGraph, and Model Context Protocol (MCP).
    • Develop scalable backend APIs and microservices to expose AI capabilities across the platform.
    • Implement and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models.
    • Evaluate, fine-tune, and deploy open-source and proprietary models for text and structured data tasks.
    • Optimize AI systems for latency, throughput, token usage, and cost efficiency.
    • Collaborate closely with product, backend, frontend, and data teams to embed AI features into user-facing workflows.
    • Build internal tooling to accelerate experimentation, prompt iteration, agent evaluation, and deployment.
    • Stay current with emerging AI research, frameworks, and agent architectures to guide platform evolution.

    Essential Skills & Technologies

    Core AI & ML

    • Strong hands-on experience with LLMs (OpenAI GPT, Anthropic Claude, Llama, Mistral, Gemini, DeepSeek, etc.).
    • Deep understanding of prompt engineering, function calling, tool use, and context management.
    • Experience building agent-based systems using LangChain, LangGraph, and MCP (Model Context Protocol).
    • Solid understanding of RAG architectures, vector databases (Pinecone, Weaviate, FAISS, Chroma), and embedding strategies.
    • Familiarity with model fine-tuning, evaluation, and serving using frameworks like Hugging Face, vLLM, or Ollama.

    Engineering & Architecture

    • Strong proficiency in Python (FastAPI preferred); experience is a plus.
    • Experience designing microservices, async systems, and event-driven architectures.
    • Cloud deployment experience (AWS, GCP, Azure, or serverless environments).
    • Databases: MongoDB / PostgreSQL / Redis.
    • Strong understanding of API design, security, and scalable system architecture.

    Optimization & Observability

    • Experience optimizing AI systems for latency, reliability, and cost.
    • Token usage management and cost optimization for LLM-based workflows.
    • Monitoring, logging, and tracing using tools such as Prometheus, Grafana, ELK, or OpenTelemetry.

    Additional Plus

    • Experience with LangServe, LlamaIndex, Haystack, or Autogen frameworks.
    • Exposure to multi-agent reasoning, evaluation matrices, or autonomous workflows.
    • Familiarity with MLOps tools (MLflow, Kubeflow, Weights & Biases).
    • Understanding of multimodal AI (documents, resumes, structured hiring data).
    • Frontend exposure (React / TypeScript) for integrating AI-driven UX.

    What You'll Bring

    • 4+ years of experience building and deploying AI/ML systems in production environments.
    • Strong background in NLP, generative AI, or applied machine learning.
    • Ability to balance innovation with system performance, reliability, and scalability.
    • Strong engineering fundamentals and experience shipping real-world AI products.
    • A builder's mindset—curious, hands-on, and driven to create high-impact AI systems.
    * This salary range is an estimation made by beBee
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