AI Engineer (Agentic AI & Voice Tech)

HYrEzy Tech Solutions; Gurugram District; On-site; INR 1,620,000 - 1,980,000; Full time

Job summary

HYrEzy Tech Solutions in Gurgaon is hiring an AI Engineer to build autonomous AI agents for supply‑chain analytics. You will architect multi‑agent workflows, enable real‑time voice interactions, and ensure deterministic outputs over structured and unstructured data.

You will work with STT/TTS, RAG pipelines, and tool‑calling across ERP/WMS data in a fast‑growing B2B platform. Strong production Python and backend experience is essential.

Qualifications

• Hands-on AI/software engineering in production
• Experience with Agentic AI systems and tool calling
• Experience with STT/TTS or voice technologies
• Strong backend Python stack and LLM APIs
• Ability to translate NL to SQL/analytical queries

Responsibilities

• Agentic Workflow Engineering: design and orchestrate multi-agent systems to automate supply chain workflows
• Voice AI Integration: real-time STT and TTS pipelines for multilingual logistics use cases
• RAG & Data Grounding: hybrid search over SQL/ERP data and unstructured docs
• Tool Calling & API Integration: connect LLM agents with internal systems and external APIs
• Latency, Cost & Eval Optimization: monitor latency and routing in production

Skills

Python

FastAPI/AsyncIO

Agentic AI

LLM APIs

Text-to-SQL

Tools

Qdrant

Pinecone

Milvus

pgvector

LangGraph

Job description

Client: Fast-Growing Supply Chain & Logistics Analytics Platform (Confidential)

Location: Gurgaon / Gurugram (Work from Office)

Experience: 2+ Years

Compensation: Up to ₹18 LPA

About The Client & Role

We are hiring for a fast-growing B2B Supply Chain Analytics & Intelligence platform based in Gurgaon that helps enterprise logistics, procurement, and operations teams automate complex decision-making using real-time data and AI.

We are looking for a hands-on AI Engineer with strong production experience in Agentic AI workflows and Speech/Voice technologies (TTS/STT). You will architect and deploy autonomous AI agents capable of querying supply chain databases, reasoning over operational bottlenecks, and interacting seamlessly with field and enterprise users via low-latency voice and conversational interfaces.

Key Responsibilities

• Agentic Workflow Engineering: Design, build, and orchestrate multi-agent and tool-calling systems (using frameworks like LangGraph, CrewAI, AutoGen, or custom LLM orchestrators) to automate supply chain workflows, exception handling, and analytics queries.
• Voice AI Integration (STT & TTS): Build and optimize real-time conversational voice pipelines utilizing Speech-to-Text (STT) and Text-to-Speech (TTS) models/APIs (e.g., Whisper, Deepgram, ElevenLabs, Sarvam, Cartesia, or WebSockets/WebRTC streaming) for multilingual/Indian-accented logistics and operations use cases.
• RAG & Data Grounding: Architect hybrid search and Retrieval-Augmented Generation (RAG) pipelines over structured SQL/ERP data and unstructured supply chain documents to ensure zero-hallucination, deterministic outputs.
• Tool Calling & API Integration: Connect LLM agents with internal analytics engines, ERP/WMS/TMS systems, and external APIs using strict schema validation (Pydantic / structured outputs).
• Latency, Cost & Eval Optimization: Monitor, benchmark, and optimize end-to-end token latency, voice turn-taking speed, and LLM routing fallbacks in production.

Must-Have Requirements (Non-Negotiable)

• Experience: 2+ years of hands-on software/AI engineering experience, with proven production deployments in Generative AI and LLM applications.
• Agentic AI Expertise: Deep, practical experience building Agentic AI systems—including multi-step reasoning, autonomous tool/function calling, memory management, state machines, and guardrails (LangGraph, LlamaIndex Workflows, CrewAI, or custom Python agent loops).
• TTS & STT Knowledge: Hands-on experience working with Text-to-Speech (TTS) and/or Speech-to-Text (STT) models, voice activity detection (VAD), audio streaming pipelines, or real-time voice agents.
• Strong Backend & Python Stack: Proficiency in Python (FastAPI / AsyncIO), vector databases (Qdrant, Pinecone, Milvus, or pgvector), and LLM APIs (OpenAI, Anthropic, Gemini, or open-weight models via vLLM).
• Structured Data & Analytics Comfort: Ability to build agents that can translate natural language into SQL/analytical queries (Text-to-SQL) or interact with complex B2B data pipelines.

Good-to-Have (Preferred)

• Prior exposure to Supply Chain, Logistics, E-commerce Ops, FinTech, or B2B Enterprise SaaS analytics.
• Experience fine-tuning or optimizing speech models for Indian languages/accents or noisy field environments.
• Familiarity with observability and evaluation tools (LangSmith, Langfuse, Arize Phoenix).

Skills: analytics,pipelines,supply chain,speech,models,data,supply,tts,stt,agentic ai,agents,generative ai,artificial intelligence