We are seeking a Principal AI Engineer with deep, hands-on experience in Large Language Models (LLMs) to lead the design, development, and deployment of enterprise-grade AI-powered automation systems across the organization.
This role goes beyond experimentation. You will own and deliver production-scale AI solutions , analyze complex internal workflows, identify high-value automation opportunities, and architect intelligent systems that materially improve efficiency, accuracy, and scalability.
This position is ideal for a seasoned engineer (10+ years) who combines strong technical depth, architectural judgment, and a product mindset , and who enjoys building practical, high-impact AI systems used at scale .
KEY RESPONSIBILITIES:
- Lead the design, development, and deployment of LLM-based automation solutions across multiple business functions.
- Work closely with cross-functional teams to define problem statements, data requirements, system boundaries, and solution approaches .
- Architect and implement end-to-end LLM systems , including:
- Prompt pipelines
- Agent-based architectures
- Retrieval-Augmented Generation (RAG) systems
- Internal AI services and APIs
- Integrate commercial and open-source LLMs (e.g., OpenAI, Anthropic, Databricks, open-source models) into enterprise systems and products .
- Drive model evaluation, prompt optimization, and system reliability improvements based on real-world usage.
- Establish and maintain monitoring, logging, and evaluation frameworks for LLM-driven applications.
- Partner with product, operations, security, and engineering teams to map workflows and identify high-ROI automation opportunities .
- Ensure all AI solutions meet enterprise standards for data privacy, security, compliance, and governance .
- Act as a technical mentor and thought leader , setting best practices for LLM engineering and applied AI.
- Stay current with advances in LLMs, agent frameworks, AI infrastructure, and applied research—and translate them into pragmatic solutions.
Basic Qualifications:
- Bachelor's degree in AI, Machine Learning, Computer Science, Statistics, or a related field
- A minimum of 8 years of professional experience in software engineering, AI, or machine learning, including a minimum of 3 years of significant hands-on work on LLM-based systems .
- Proven, production experience with Large Language Models , including:
- Prompt engineering and prompt optimization
- Model integration and orchestration
- Evaluation and reliability tuning
- Strong proficiency in Python and modern AI/ML frameworks and libraries (e.g., PyTorch, TensorFlow, LangChain, similar ecosystems).
- Solid background in deep learning and applied machine learning .
- Strong analytical and mathematical foundation relevant to ML systems.
- Experience designing systems that balance performance, scalability, cost, and accuracy .
- Ability to communicate complex technical concepts clearly to technical and non-technical stakeholders .
- Strong written and spoken English.
Preferred Qualifications:
- Master's degree in AI, Machine Learning, Computer Science, Statistics, or a related field (or equivalent professional experience).
- PhD or additional advanced degree in AI, Machine Learning, Computer Science, Statistics, or related fields.
- Experience building meaningful visualizations and explaining model behavior and results.
- Background in data mining, analytics, or decision-support systems .
- Experience with regression, supervised and unsupervised learning , and applied ML in production contexts.
- Prior experience with automotive, IoT, or large-scale industrial data .
- Contributions to open-source projects or published technical work.
- Experience operating AI systems under enterprise governance, security, and compliance constraints .