Lead Engineer, AI Platforms

Overview

Lead AI engineer building enterprise LLM, RAG, and agentic solutions.

Key Responsibilities

• platform integration
• llm engineering
• team leadership
• ai standards
• agent development
• solution evaluation

Tasks

-Integrate with Enterprise Platforms: Embed AI capabilities into OMS, CRM, loyalty, and digital platforms, ensuring seamless user and operational experiences. -Engineer LLM Applications: Develop fine-tuned and optimized large language model applications with retrieval-augmented generation (RAG) pipelines. -Lead & Mentor: Guide a team of AI engineers and contribute to the enterprise AI strategy while remaining hands-on in technical delivery. -Establish AI Engineering Practices: Define standards for AI model deployment, observability, safety, and compliance. -Build Agentic Models: Design and develop AI agents capable of reasoning, planning, and executing multi-step tasks. -Evaluate AI Solutions: Analyze and benchmark AI platforms, LLMs, and agent frameworks for enterprise use. -Governance & Security: Implement guardrails, privacy protections, and compliance controls for AI-enabled applications. -Collaborate Across Teams: Partner with Product, Digital Engineering, and Data Science to co-create AI-powered features and workflows.

Requirements

• phd
• python
• azure
• mlops
• llms
• ai governance

What You Bring

-Bachelor’s degree in Computer Science, Engineering, or related field; Master’s or PhD preferred. -Background in AI governance, responsible AI, or applied ethics. -Publications, patents, or open-source contributions in AI/ML. -Hands-on experience with RAG pipelines, embeddings, and vector search in production. -Strong understanding of cloud-native AI services (Azure preferred). -Observability: Langfuse, Weights & Biases, Application Insights for model monitoring. -Background in regulated industries (aviation, logistics, finance, or hospitality). -8+ years of professional experience in software engineering, AI/ML, or data platforms. -Cloud Platforms: Azure AI/ML services, Azure OpenAI, AWS Bedrock, or GCP Vertex AI. -Experience with multimodal AI (vision, speech, structured data). -LLMs: OpenAI GPT, Anthropic Claude, LLaMA, Falcon, or similar. -Vector Databases: Pinecone, Weaviate, Redis Vector, or Azure Cognitive Search. -Proven expertise in building and deploying LLM-powered applications and agentic AI models. -Familiarity with aviation, logistics, or operational technology domains. -MLOps: MLflow, Azure Machine Learning, or equivalent model lifecycle tools. -Security: OAuth 2.0, RBAC, data privacy, compliance frameworks (GDPR, PCI). -AI/ML Frameworks: LangChain, LlamaIndex, Semantic Kernel, Hugging Face. -Programming Languages: Python (preferred), TypeScript/Node.js for integrations. -Experience guiding teams, delivering complex AI projects, and driving innovation.

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Benefits

-Paid time off -Tuition reimbursement -Health Savings Account -Identity Theft and Legal Services -Disability Insurance -Paid Maternity Leave -Critical Illness, Hospital Indemnity and Accident Insurance -Training and Development -Medical/prescription drug, dental, and vision Insurance -Life Insurance -Flexible Spending Accounts -Employee Assistance Program (EAP) & Perks

About Signature Aviation

-With a rich history of providing exceptional fuel services, ground handling, and aircraft maintenance, the company serves thousands of clients worldwide. -Operates across major airports, offering comprehensive services that cater to both private and commercial aviation. -The company's expertise spans fueling, maintenance, concierge services, and more, making it a go-to partner for aviation professionals. -Noteworthy for their innovation, Signature Aviation also invests in sustainable technologies and solutions that benefit both their clients and the environment. -With an extensive global footprint, Signature Aviation is consistently ranked among the top service providers in the aviation sector.

Sector Specialisms