AI Engineer – LLMs, AI Agents & ML Solutions

Key Responsibilities

• Architect, train, fine-tune, and deploy custom LLMs and autonomous AI Agent workflows using LangChain, LlamaIndex, AutoGen, or CrewAI.
• Implement enterprise RAG (Retrieval-Augmented Generation) pipelines integrated with Vector Databases (Pinecone, Qdrant, ChromaDB, pgvector).
• Design and build end-to-end Machine Learning models for predictive analytics, natural language processing (NLP), and process automation.
• Develop production RESTful & gRPC APIs wrapping AI models using Python, FastAPI, PyTorch, and Hugging Face Transformers.
• Optimize AI model inference latency, quantization, and token efficiency for cloud deployments on Azure AI / AWS SageMaker.
• Ensure enterprise AI governance, prompt security, hallucination mitigation, guardrails (NeMo Guardrails), and compliance standards.
• Collaborate with enterprise solution architects and client leaders to translate business workflows into scalable AI agent systems.

Solutions You Will Sell

Target Customers & Markets

Preferred Skills & Qualifications

• 3–7 years of hands-on experience in AI, Machine Learning, NLP, and Deep Learning engineering.
• Deep expertise with Python, PyTorch / TensorFlow, Hugging Face Transformers, LangChain, and LlamaIndex.
• Hands-on experience building Autonomous AI Agents (CrewAI, AutoGen, LangGraph) and function-calling architectures.
• Solid experience with Vector Databases (Pinecone, Qdrant, Milvus, pgvector) and embedding techniques.
• Production experience deploying AI models on Azure OpenAI, AWS SageMaker, or vLLM containerized microservices.
• Strong foundation in MLOps, model evaluation, monitoring (MLflow, Weights & Biases), and CI/CD for AI systems.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related technical field.

Key Performance Indicators (KPIs)

Success Profile

• Innovator passionate about cutting-edge Generative AI, Multi-Agent Orchestration, and LLM frameworks
• Strong analytical thinker capable of designing robust software architectures around non-deterministic AI models
• Proactive communicator capable of explaining complex AI capabilities to executive stakeholders
• Continuous learner keeping pace with rapid advancements in AI models and MLOps tools

Why Join HG Infotech?

• Ground-floor opportunity to lead enterprise AI Agent implementations for global enterprise clients
• Direct access to cutting-edge LLMs, GPU infrastructure, and Microsoft Azure AI partnership resources
• Work directly with founders and senior technology architects across Singapore, Malaysia, and India
• High-growth role with competitive compensation, performance bonuses, and continuous AI research support