AI Integration Engineer | 2026HP02007/#gd8QNfnx at Mindverse Consulting Services Limited

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

27 May, 26

Salary

0.0

Posted On

26 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

API Mastery, Vector DBs, LLM Providers, Python, FastAPI, Pydantic, LangGraph, Moltbot, OpenClaw, RAG Pipeline Engineering, AIOps, LLMOps, Cognitive Architecture Design, Prompt Engineering, Guardrail Engineering, Kubernetes

Industry

IT Services and IT Consulting

Description

Job Summary We are 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. Job 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. Essential Skills · 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. Background Check required No criminal record Others Work mode- Hybrid model working (3 days work from office) Office Location-Rai Durg, Hyderabad Interview rounds-3-4 rounds of interviews.

Responsibilities

The engineer will integrate advanced AI models into operational systems by building and maintaining the necessary tools, APIs, and middleware for autonomous agents. Key tasks include developing RAG pipelines, managing data ingestion into Vector Databases, and ensuring robust connectivity for agent workflows.