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.
