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AI Integration Engineer- Hyderabad

Actively Reviewing the Applications

HYrEzy Tech Solutions

India, Telangana, Hyderabad Full-Time On-site INR 18–32 LPA

Posted 2 weeks ago • Apply by June 7, 2026

Job Description

Role: AI Integration Engineer

Location: Rai Durg, Hyderabad
Work mode- Hybrid model working (3 days work from office)
Experience: 5 - 8 Years (Minimum 5 years- AI Integration)
Mandatory Skills: Vector DBs (Pinecone, Milvus, or Qdrant) and LLM providers, LLM Ops, LangGraph, Moltbot, Advanced Python, OAuth
Budget: 18 - 32 LPA
Qualification: Bachelor of Engineering - Bachelor of Technology (B.E./B.Tech.)
Notice period: Immediate / early joiners (Max. 15-30 days)
Interview Process: 2 - 3 Technical rounds

Important Note

Candidates from background in Fintech, Logistic are preferred
We are currently prioritizing immediate / early joiners (maximum 15 - 30 days- notice period above 30 days will be automatically rejected.).
All mandatory technical skills must be clearly highlighted within the project descriptions in your resume, not just listed in the Skills or Roles & Responsibilities sections .

Position Overview

IC Markets is seeking a high-velocity AI Integration Engineer to join our Agentic AI Task Force. Your mission is to take advanced AI models and embed them deeply into our operational DNA. You will be responsible for the "pipes", ensuring our autonomous agents have seamless access to the tools, data, and communication channels they need to function as "Super Employees."

This role is for a builder who thrives on the "how", turning a high-level architectural vision into a robust, integrated reality using frameworks like Moltbot and OpenClaw, and others.

Key Responsibilities

Tool & API Integration: Build and maintain the "tools" (function calling) that agents use to interact with our CRM, support ticketing systems, and internal databases.
RAG Pipeline Engineering: Develop and optimize Retrieval-Augmented Generation (RAG) pipelines to ensure agents have real-time, accurate context from our knowledge bases.
Connectivity & Orchestration: Implement the middleware that connects Agentic workflows to front-end support interfaces (Chat, Email, etc.).
Data Ingestion & Vectorization: Manage the lifecycle of data within our Vector Databases, ensuring high-quality embedding and retrieval performance.
Monitoring & Latency Optimization: Implement observability for AI calls (tracking tokens, costs, and response times) to ensure the "super employee" is as fast as a human, or faster.
Deployment & CI/CD: Manage the deployment of agentic microservices, ensuring that AI updates don't break existing support workflows.

Qualifications

API Mastery: Expert knowledge of RESTful APIs, Webhooks, and secure authentication protocols (OAuth, etc.).
The AI Stack: Hands-on experience with Vector DBs (Pinecone, Milvus, or Qdrant) and LLM providers (OpenAI, Anthropic, or local models).
Programming: Advanced Python (FastAPI, Pydantic) and experience with streaming data/WebSockets.
Framework Experience: Practical experience with LangGraph, Moltbot, or similar tool-calling frameworks.
AIOps: Familiarity with LLMOps tools for monitoring model performance and drift in production.

Additional Qualifications

Cognitive Architecture Design: Ability to design Multi-Agent Orchestration (MAO) patterns (e.g., Manager-Worker, Peer-to-Peer, or Hierarchical teams).
Advanced Prompt Engineering & Optimization: Mastery of DSPy (Programming instead of Prompting), chain-of-thought, and automatic prompt optimization.
Guardrail & Safety Engineering: Implementing frameworks like NeMo Guardrails or LlamaGuard to ensure agents don't hallucinate or leak sensitive trading data.
Evaluation (Eval) Frameworks: Building custom "Eval" suites using Ragas or TruLens to mathematically measure the accuracy and reliability of agent reasoning.
State Management: Expertise in managing long-term memory and persistent state across complex, multi-day agentic "tasks."
Infrastructure: Experience with Docker, Kubernetes, and cloud-native serverless functions..

Why Join ?

Opportunity to lead transformative initiatives, modernizing legacy systems and shaping the future of trading technology.
Work with cutting-edge technologies in a dynamic, fast-paced environment.
Competitive compensation, professional growth opportunities, and the chance to work with industry-leading experts

Skills: ai integration engineer,llm providers,vector dbs (pinecone, milvus, or qdrant)