AI Engineer (Senior/Mid Level)
Company Description
Infinite Control is a technology-focused company specializing in advanced automation and intelligent systems. The organization is committed to leveraging artificial intelligence to solve complex real-world problems and improve operational efficiency for its clients. Team members collaborate across disciplines to design, build, and deploy AI-driven solutions that deliver measurable impact
Job Description
We are looking for an AI Engineer to transform complex business problems into reliable, secure, and production-ready AI solutions. You will design and develop enterprise AI applications, including RAG systems, AI agents, document intelligence pipelines, and AI-powered business automation, integrated with ERP, CRM, APIs, and other enterprise systems.
Key Responsibilities
Design and build enterprise-grade LLM applications, RAG systems, AI agents, and document understanding solutions.
Develop agentic workflows that use tools and APIs, manage state and memory, and support human-in-the-loop escalation.
Integrate AI solutions with ERP, CRM, databases, and enterprise APIs.
Transform AI prototypes and proof-of-concepts into scalable, reliable, secure, and production-ready applications.
Establish evaluation and testing processes to measure retrieval quality, tool-call accuracy, task completion, hallucinations, and regressions.
Implement safeguards against AI security risks such as prompt injection, excessive agency, tool abuse, and data leakage
Requirements
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Strong experience with LLM application development, including prompt/context engineering, structured outputs, and function/tool calling.
Hands-on experience with Advanced RAG, including chunking, metadata filtering, vector search, and retrieval optimization.
Experience designing AI agents and agentic workflows, including planning, tool use, state, and memory.
Ability to determine when to use deterministic workflows vs. autonomous agents based on business and reliability requirements.
Strong understanding of AI evaluation and security, including the principle that LLMs are untrusted components and must never act as the authorization layer.
Strong Python development skills with experience in Git and API integration.
Experience with FastAPI or similar backend frameworks.
Strong knowledge of PostgreSQL.
Experience with async programming and background processing.
Understanding of production software engineering, reliability, testing, scalability, and maintainability.
Nice to Have
Frameworks: LangGraph, LlamaIndex, Hugging Face, vLLM, Ollama.
Data & Knowledge: pgvector, vector databases, Knowledge Graphs.
Advanced ML: LoRA/QLoRA fine-tuning, quantization, PyTorch.
Experience deploying and operating LLM/AI systems in production.