Artificial Intelligence Engineer

Nexa Office Infosystems; Coimbatore District; On-site; INR 1,500,000 - 2,800,000; Full time

Job summary

Nexa Office Infosystems is seeking an experienced AI Engineer to design and deploy Generative AI and multimodal AI solutions. You will build, train, and optimize LLMs for real-time copilots and agents, integrating OCR, audio, and image processing capabilities across AWS and Azure environments.

The role emphasizes building scalable AI copilots, agentic reasoning, and highly efficient pipelines with WebRTC-based real-time interactions, FP32/FP16 optimization, and robust Linux deployments.

Qualifications

• Expert-level Python programming.
• Strong hands-on experience with Generative AI & LLMs.
• Experience with LLAMA or equivalent models.
• Hands-on experience with Vector Databases (Qdrant DB, Chroma DB, FAISS, Pinecone, Milvus).
• Strong understanding of GPU computing, memory optimization, and performance tuning.
• Experience with AWS GPU EC2 and Azure GPU services.
• Solid experience with Deep Learning frameworks (PyTorch, TensorFlow).
• Strong knowledge of Image Processing.
• Hands-on experience with Audio Processing, including Whisper.
• Experience building real-time audio pipelines using WebRTC.
• Proficiency in Linux environments.
• Working knowledge of SQL databases.

Responsibilities

• Design, develop, and optimize Python-based AI applications for Generative AI use cases.
• Build, fine-tune, and deploy LLMs (LLAMA, OpenAI, Mistral, etc.).
• Develop and standardize AI Copilot frameworks.
• Build Agentic AI systems with multi-agent reasoning, tool calling, and orchestration.
• Design and manage RAG pipelines using vector databases.
• Implement Deep Learning models for image processing and multimodal AI.
• Perform image preprocessing, OCR, document AI, and vision model integration.
• Develop audio processing pipelines, including Whisper.
• Build real-time voice & AI interaction systems using WebRTC.
• Optimize workloads on AWS & Azure GPU instances; manage GPU/memory.
• Develop scalable ETL pipelines for data ingestion, embeddings, and training workflows.
• Deploy and maintain AI services in Linux environments.
• Collaborate with cross-functional teams to deliver production-ready AI systems.

Skills

Python programming

Generative AI

LLMs

Multi-modal AI

GPU optimization

AWS/Azure GPU services

PyTorch/TensorFlow

Linux

Real-time systems (WebRTC)

OCR/Docs processing

Audio processing (Whisper)

Image processing

Tools

Qdrant DB

Chroma DB

FAISS

Pinecone

Milvus

Job description

About the Role

We are seeking an experienced AI Engineer with strong expertise in Generative AI, Large Language Models (LLMs), Agentic AI, and Multimodal AI systems (Text, Image, and Audio).

The role focuses on building AI Copilot platforms, real-time AI assistants, and GPU-optimized AI solutions across AWS and Azure cloud environments.

Key Responsibilities

• Design, develop, and optimize Python-based AI applications for Generative AI use cases.
• Build, fine-tune, and deploy LLMs (LLAMA, OpenAI, Mistral, etc.).
• Develop and standardize AI Copilot frameworks.
• Build Agentic AI systems with multi-agent reasoning, tool calling, and orchestration.
• Design and manage RAG pipelines using Qdrant DB, Chroma DB, and other Vector Databases.
• Implement Deep Learning models for image processing and multimodal AI.
• Perform image preprocessing, OCR, document AI, and vision model integration.
• Develop audio processing pipelines, including:
  • Speech-to-Text (STT) using Whisper
  • Audio preprocessing and noise handling
• Build real-time voice & AI interaction systems using WebRTC.
• Optimize workloads on AWS & Azure GPU instances, including GPU and memory management.
• Develop scalable ETL pipelines for data ingestion, embeddings, and training workflows.
• Deploy and maintain AI services in Linux-based environments.
• Collaborate with cross-functional teams to deliver production-ready AI systems.

Must-Have Skills

• Expert-level Python programming.
• Strong hands‑on experience with Generative AI & LLMs.
• Experience working with LLAMA or equivalent models.
• Hands‑on experience with Vector Databases:
  • Qdrant DB
  • Chroma DB
  • FAISS, Pinecone, Milvus, or similar
• Strong understanding of GPU computing, memory optimization, and performance tuning.
• Experience with AWS GPU EC2 and Azure GPU services.
• Solid experience with Deep Learning frameworks (PyTorch, TensorFlow).
• Strong knowledge of Image Processing.
• Hands‑on experience with Audio Processing, including Whisper.
• Experience building real-time audio pipelines using WebRTC.
• Proficiency in Linux environments.
• Working knowledge of SQL databases.

Good-to-Have (Bonus) Skills

• Experience with LLM orchestration frameworks:
  • LangChain
  • LlamaIndex
  • Haystack
• Experience with Agentic AI frameworks.
• API development using FastAPI, Streamlit, or similar.
• Experience implementing CI/CD pipelines for AI/ML workloads.
• Knowledge of ETL pipelines and data engineering.
• Familiarity with multimodal LLMs (text + image + audio).
• Experience across AWS services (S3, API Gateway, EC2) and Azure services.
• Exposure to multiple GenAI models (OpenAI, LLAMA, Mistral, Google Bard, etc.).

Nice-to-Have

• Experience with real-time AI assistants and voice bots.
• Knowledge of RAG architectures, AI security, and governance.
• Containerization experience (Docker, Kubernetes).
• MLOps
• Monitoring, logging, and observability for AI systems.