AI Engineer

Responsibilities

• Build agentic AI systems: tool-calling agents, multi-step workflow automation, and human-in-the-loop flows
• Develop GenAI applications using LLM APIs, RAG pipelines, vector databases, and prompt and evaluation frameworks
• Implement voice AI and WhatsApp/chat agents, including STT/TTS, telephony, and conversational flow design
• Integrate AI services with client systems through REST APIs, webhooks, CRMs, and databases
• Deploy and evaluate small or local language models where cost, privacy, or data-residency requirements apply
• Build document digitization and OCR pipelines in collaboration with the team
• Monitor quality, latency, and cost in production, and iterate on hallucination control, guardrails, and accuracy
• Contribute to client demos, POCs, technical scoping, and documentation
• Use AI-assisted development tools to ship faster and share good practices with the team

Requirements

• 2+ years of hands-on experience building AI/ML-powered applications (not only coursework or notebooks)
• Strong Python; working knowledge of FastAPI or Flask
• Practical experience with LLM APIs (OpenAI, Anthropic, Gemini, or open-source models)
• Built at least one RAG system or agent end to end, including embeddings and a vector store (pgvector, Pinecone, Qdrant, FAISS, etc.)
• Prompt engineering, structured outputs, and function/tool calling
• Git, REST APIs, JSON, SQL, and Docker basics
• Clear written and verbal communication; able to explain AI limits to non-technical clients