Lead AI Engineer – Generative & Agentic AI

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
🏢 Work Mode: 5 Days Work From Office
💼 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 Data Scientists – Generative AI (Engineer & Lead) to join our AI Engineering team in Chennai.
The ideal candidate should have strong hands-on experience building and deploying enterprise-grade Generative AI and Agentic AI applications using LLMs, 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 production-grade Generative AI and Agentic AI applications
• Develop end-to-end GenAI pipelines from data preparation through deployment and monitoring
• Build scalable RAG pipelines, semantic search, hybrid search, embeddings, and reranking solutions
• Integrate LLMs such as GPT, Claude, LLaMA, and Mistral into production applications
• Develop AI workflows using LangChain, LlamaIndex, Hugging Face, OpenAI APIs, Anthropic APIs, and AutoGen
• Build multi-agent AI workflows and enterprise Agentic AI solutions
• Work with vector databases including Pinecone, FAISS, Milvus, Weaviate, and ChromaDB
• Optimize model inference, latency, throughput, and infrastructure cost using vLLM, Ollama, Quantization, PEFT, LoRA, and QLoRA
• Develop AI microservices, REST APIs, GraphQL services, and Kafka-based services
• Deploy AI workloads using Docker, Kubernetes, Azure, AWS, or GCP
• Implement MLOps/LLMOps, CI/CD, monitoring, observability, and model lifecycle management
• Build multimodal AI solutions involving text, vision, speech, audio, image, and video
• Collaborate with Product, Engineering, Data Science, and Business teams
👨 💻 For Lead Candidates
• Own technical architecture for enterprise GenAI solutions
• Provide technical leadership and mentorship
• Conduct code reviews and establish AI engineering best practices
• Lead enterprise-scale AI initiatives and drive production adoption
🔑 Required Skills
Programming & ML: Python, SQL, Machine Learning, Deep Learning, PyTorch, TensorFlow
LLMs: GPT, Claude, LLaMA, Mistral
GenAI: Generative AI, Agentic AI, AI Agents, Multi-Agent Systems, Prompt Engineering
Frameworks: LangChain, LlamaIndex, Hugging Face Transformers, OpenAI API, Anthropic API, AutoGen
RAG & Search: RAG, Embeddings, Chunking, Semantic Search, Hybrid Search, Reranking
Vector Databases: Pinecone, FAISS, Weaviate, Milvus, ChromaDB
Model Optimization: vLLM, Ollama, Quantization, PEFT, LoRA, QLoRA
Cloud: Azure AI Foundry, Azure AI Search, Azure OpenAI, AWS, Azure, GCP
Infrastructure: Docker, Kubernetes, REST APIs, GraphQL, Kafka, Microservices, CI/CD, MLOps, LLMOps, AI Observability
⭐ Preferred
✔ Production-scale GenAI platform development
✔ Enterprise Agentic AI experience
✔ Multimodal AI experience
✔ Enterprise AI architecture
✔ Secure and scalable cloud-native AI solutions
📩 Interested candidates can apply with their updated profile.
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Work arrangement
No