AI Engineer - HN/HCM

What You’ll Do

We are building an enterprise-grade Agentic AI platform powered by LLMs, RAG, and custom orchestration. Unlike typical GenAI teams, we do not rely on a single framework. We design systems from first principles and build production-ready AI systems, not demos.

• Architect and develop specialized, enterprise-grade AI Agents capable of reasoning, tool-calling, automation, and long-term memory.
• Implement intelligent workflows using RAG, embeddings, ontology-based reasoning, and AI memory structures.

Primary Skills (Must-have)

LLM & RAG Systems

• Agentic workflows: planning, reflection, self‑improvement loops
• Build production RAG pipelines and LLM applications
• End-to-end pipelines: data → embeddings → retrieval → LLM reasoning → evaluation → deployment
• Experience with embeddings and vector DBs (Qdrant, FAISS, Pinecone, pgvector)
• Vector search & retrieval optimization

Backend Engineering

• Strong Python
• API development (FastAPI/Flask)
• Scalable backend systems, async, caching

System Design

• End-to-end AI system design
• Agent memory custom design
• Knowledge base solution design
• Performance tuning (retrieval, prompts, caching)

Secondary Skills

• Framework exposure: LangChain, LlamaIndex.
• Cloud: Hand-on experience at least on cloud service GCP/AWS/Azure
• MLOps: Docker, Kubernetes, MLflow
• Google Vertex AI /Azure AI Foundry/ Amazon Bedrock
• Running self-hosted LLMs
• Fine-tuning LLMs directly on cloud GPUs
• Automated evaluation pipelines: grounding, hallucination detection, drift analysis
• Deploy AI systems with monitoring, observability, and safety guardrails

What You Bring

• 4+ years in Applied AI / ML Engineering with production systems
• Strong Python skills for AI pipelines and automation
• Experience building LLM-based products, RAG systems, or Agentic workflows
• Knowledge of vector DBs, embeddings, retrieval optimization
• Familiarity with MLOps tools (MLflow, Helm, Kubernetes)
• Experience with LLMs (OpenAI, HuggingFace, Ollama)
• Ability to operate in a fast-paced engineering team

Why Join Us

• Work with cutting-edge AI models and deep-tech innovation
• Build specialized agentic systems for enterprise workflows
• Experiment with fine-tuning, self-hosting, embeddings, multimodal models
• Fast-growing AI team with significant career growth
• Collaborate with engineers from Amazon, Microsoft, Google
• Direct impact: systems you build go into production