Lead Generative AI / Agentic AI Engineer

Company Description ThreatXIntel is a growing Cybersecurity, IT Staffing, and Consulting company delivering end-to-end technology and security solutions.

We are hiring for our corporate client. ThreatXIntel is the official hiring partner for this requirement. 📍

Location: Chennai (Onsite – 5 Days/Week) 💼

Employment Type: Full-Time 🎯

Experience:

• Engineer: 5–8 Years
• Lead: 8–12 Years ⏳

Notice Period: Immediate to 15 Days Preferred

About the Role We are looking for experienced and passionate

Data Scientists – Generative AI (Engineer & Lead) to join our AI Engineering team in Chennai. The ideal candidate will have strong hands-on experience in designing, developing, and deploying enterprise-grade

Generative AI and

Agentic AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Multimodal AI, and cloud-native AI infrastructure. You will work on next-generation AI solutions involving LLM orchestration, RAG pipelines, vector databases, model serving, AI microservices, MLOps/LLMOps, and scalable cloud deployments.

Key Responsibilities

• Design, build, and deploy enterprise-grade Generative AI and Agentic AI applications.
• Build end-to-end GenAI pipelines from data collection, preprocessing, model development, evaluation, deployment, and monitoring.
• Develop scalable Retrieval-Augmented Generation (RAG) pipelines for enterprise use cases.
• Integrate Large Language Models (GPT, Claude, LLaMA, Mistral) into production systems.
• Develop AI workflows using LangChain, LlamaIndex, Hugging Face, OpenAI APIs, Anthropic APIs, and AutoGen.
• Design and implement multi-agent AI workflows and enterprise Agentic AI solutions.
• Build embedding pipelines, semantic search, hybrid search, reranking, and document intelligence solutions.
• Implement vector database solutions using Pinecone, FAISS, Milvus, Weaviate, and ChromaDB.
• Optimize model inference, latency, throughput, and infrastructure cost using vLLM, Ollama, quantization, PEFT, LoRA, and QLoRA.
• Develop scalable REST APIs, GraphQL services, Kafka-based services, and AI microservices.
• Deploy AI workloads using Docker, Kubernetes, and Azure, AWS, or GCP.
• Implement enterprise MLOps and LLMOps practices, including CI/CD, testing, monitoring, observability, and model lifecycle management.
• Develop multimodal AI solutions involving text, vision, image, speech, audio, and video generation using models such as Stable Diffusion and DALL·E.
• Collaborate with Product, Engineering, Data Science, and Business teams to deliver enterprise AI solutions.
• For Lead roles: Drive technical architecture, provide technical leadership, mentor AI engineers, perform code reviews, define AI best practices, and lead enterprise-scale AI initiatives.

Required Skills Programming & AI

• Python
• SQL
• Machine Learning
• Deep Learning
• PyTorch
• TensorFlow

Large Language Models

• GPT
• Claude
• LLaMA
• Mistral

Generative AI

• Generative AI
• Agentic AI
• AI Agents
• Multi-Agent Systems
• Prompt Engineering

AI Frameworks

• LangChain
• LlamaIndex
• Hugging Face Transformers
• OpenAI API
• Anthropic API
• AutoGen

RAG & Search

• Retrieval-Augmented Generation (RAG)
• Embeddings
• Chunking
• Semantic Search
• Hybrid Search
• Reranking

Vector Databases

• Pinecone
• FAISS
• Weaviate
• Milvus
• ChromaDB

Model Deployment & Optimization

• vLLM
• Ollama
• Model Quantization
• PEFT
• LoRA
• QLoRA

Multimodal AI

• Stable Diffusion
• DALL·E
• Image Generation
• Vision AI
• Speech AI
• Audio AI
• Video Generation

Cloud & Azure

• Azure AI Foundry
• Azure AI Search
• Azure OpenAI
• AWS
• Azure
• GCP

DevOps & Infrastructure

• Docker
• Kubernetes
• REST APIs
• GraphQL
• Kafka
• Microservices
• CI/CD
• MLOps
• LLMOps
• AI Observability
• Model Monitoring

Preferred Qualifications

• Experience building production-scale Generative AI platforms.(PYTHON)
• Experience with enterprise Agentic AI systems.
• Hands-on experience with multimodal AI applications.
• Strong understanding of enterprise AI architecture.
• Experience with secure and scalable cloud-native AI solutions.