Senior Associate – Conversational AI / RAG Engineer

Elfonze Technologies; Hyderabad, Bengaluru; Hybrid; INR 2,600,000 - 3,800,000; Full time

Job summary

Elfonze Technologies in Hyderabad, Bangalore, India, is seeking a Senior Associate – Conversational AI / RAG Engineer to design, build, and deploy enterprise-grade AI solutions powered by LLMs, RAG, and knowledge platforms.

The ideal candidate will work on end-to-end RAG architectures, document ingestion, embedding, and semantic search, while integrating OpenAI, Azure OpenAI, Gemini, Claude, and open-source models into enterprise apps.

Qualifications

• Hands-on experience building enterprise-grade conversational AI solutions and intelligent assistants.
• Expertise in retrieval-augmented generation, knowledge platforms, and vector databases.
• Proficient in Python, FastAPI, REST APIs, and cloud-native development.

Responsibilities

• Design and develop conversational AI applications, virtual assistants, and enterprise copilots.
• Build multi-turn experiences with memory and personalization.
• Implement end-to-end RAG architectures, ingestion, embedding, and retrieval pipelines.
• Integrate AI solutions with enterprise apps and APIs, optimize relevance and grounding.
• Develop AI microservices with secure backend systems and governance.
• Set up monitoring, observability, and evaluation frameworks for model usage and user satisfaction.

Skills

Conversational AI

Enterprise Chatbots

Virtual Assistants

Multi-turn Conversations

Context Management

RAG & Knowledge

Semantic Search

Vector Search

LLM Frameworks

LangChain

LangGraph

Semantic Kernel

CrewAI

Python

FastAPI

REST APIs

SQL

Git

Vector Databases

Pinecone

Qdrant

Weaviate

PGVector

FAISS

AWS Bedrock

LLMOps

Evaluation & Observability

Enterprise knowledge integration

Tools

LangChain

LangGraph

Semantic Kernel

CrewAI

Python

FastAPI

REST APIs

SQL

Git

Pinecone

Qdrant

Weaviate

PGVector

FAISS

AWS Bedrock

Docker

Kubernetes

Job description

Senior Associate – Conversational AI / RAG Engineer

Hyderabad, Bangalore, India | Posted on 09/22/2026

Role: Senior Associate – Conversational AI / RAG Engineer

Role Summary : We are looking for a highly skilled Conversational AI / RAG Engineer to design, build, and deploy enterprise-grade conversational AI solutions powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Knowledge Intelligence platforms.

The ideal candidate will have hands‑on experience building intelligent assistants, enterprise search solutions, knowledge bots, and AI copilots that leverage internal and external data sources to deliver accurate, context‑aware responses. This role requires strong expertise in AI engineering, information retrieval, prompt engineering, vector databases, and cloud‑native application development.

Key Responsibilities:

• Conversational AI Development
• Design and develop conversational AI applications, virtual assistants, and enterprise copilots.
• Build multi‑turn conversational experiences with contextual memory and personalization.
• Develop intent‑based and GenAI‑powered chatbot solutions.
• Integrate conversational AI solutions with enterprise applications, APIs, and business workflows.
• Optimize conversation flows, response quality, and user experience.
• Retrieval‑Augmented Generation (RAG)
• Design and implement end‑to‑end RAG architectures.
• Build document ingestion, chunking, embedding, indexing, and retrieval pipelines.
• Implement semantic search and knowledge retrieval solutions across structured and unstructured data.
• Optimize retrieval relevance, grounding accuracy, and response quality.
• Develop scalable enterprise knowledge assistants leveraging internal content repositories.
• LLM Integration & Prompt Engineering
• Integrate OpenAI, Azure OpenAI, Gemini, Claude, and open‑source models into enterprise applications.
• Design prompt templates and orchestration workflows.
• Develop strategies to minimize hallucinations and improve answer fidelity.
• Conduct prompt tuning and response evaluation to enhance system performance.
• AI Application Engineering
• Build AI microservices and APIs using Python and FastAPI.
• Develop scalable and secure backend systems supporting AI workloads.
• Implement authentication, authorization, and enterprise security standards.
• Optimize inference performance and operational efficiency.
• Evaluation, Monitoring & Governance
• Implement monitoring and observability mechanisms for conversational AI applications.
• Track retrieval performance, response quality, latency, user feedback, and model usage.
• Develop evaluation frameworks for grounding, correctness, relevance, and user satisfaction.
• Follow Responsible AI, security, privacy, and governance standards.

Required Skills:

• Conversational AI
• Enterprise Chatbots
• Virtual Assistants
• Multi‑turn Conversations
• Conversational Design
• Context Management
• RAG & Knowledge Systems
• Retrieval‑Augmented Generation (RAG)
• Semantic Search
• Hybrid Search
• Knowledge Retrieval
• Vector Search Optimization
• AI / LLM Frameworks
• LangChain
• LangGraph
• Semantic Kernel
• CrewAI (Preferred)
• Programming
• Python
• FastAPI
• REST APIs
• SQL
• Git
• Vector Databases & Search
• Pinecone
• Qdrant
• Weaviate
• PGVector
• FAISS
• AWS Bedrock
• Experience building enterprise knowledge assistants.
• Experience integrating SharePoint, Microsoft 365, Confluence, ServiceNow, Salesforce, or other enterprise knowledge sources.
• Knowledge of Agentic AI and multi‑agent architectures.
• Experience with LLMOps, evaluation frameworks, and AI observability tools.
• Cloud certifications (Azure/AWS/GCP).
• Experience deploying containerized AI applications using Docker and Kubernetes.