Principal AI Engineer

ForeFlight • Austin, TX

1d

About The Position

Jeppesen ForeFlight is hiring a Principal AI Engineer to join our RADAR (Reporting, Analytics, Data, AI & Research) team. Reporting to the VP of Data Analytics, you will serve as the founding technical leader for an internal AI products function, designing and building the intelligent knowledge infrastructure that connects our executive leadership team, their organizations, and eventually the entire Jeppesen ForeFlight workforce to the information, context, and workflows they need to operate at peak effectiveness. This is not a research role or a one-off automation job. You will architect and build a scalable, enterprise-grade platform that captures institutional knowledge, models organizational context, and surfaces the right information to the right people at the right time, all integrated with the communication platforms and operational systems our teams already use. Think of it as building the intelligent connective tissue of the organization: a structured, AI-powered knowledge graph that grows smarter with every interaction and scales across every function. You will build on top of agentic platforms (Claude, Codex, Claude and OpenAI Agent SDKs, Cline) and complementary AI ecosystems, connecting them to enterprise systems via the Model Context Protocol (MCP) and custom integrations. Starting with the executive leadership team, you will prove the model, then expand it across the company, ultimately growing a team and partnering with Product to translate internal AI capabilities into customer-facing products. The ideal candidate has deep experience building knowledge-driven AI systems, has led enterprise AI transformations, and combines hands-on technical execution with the strategic vision and communication skills to influence at the C-suite level. You are an endlessly curious problem solver who builds products and teams that bring AI to humans and bring knowledge to AI.

Requirements

• 15+ years of professional experience in software development, AI/ML, or technology leadership, with a significant track record of shipping AI-powered products and platforms in enterprise settings.
• Demonstrated experience leading enterprise AI transformation, driving adoption of AI systems that fundamentally change how organizations operate, make decisions, and manage knowledge.
• Deep expertise in knowledge management systems, knowledge graphs, or organizational intelligence platforms - understanding how to model, capture, and activate institutional knowledge at scale.
• Strong proficiency in Python, Rust, and/or TypeScript for building production-grade applications and AI pipelines.
• Hands-on experience building applications that use LLM APIs (Anthropic Claude API, OpenAI API, or similar) including tool use, function calling, structured outputs, and multi-turn orchestration.
• Experience integrating AI systems with external APIs, databases, and SaaS platforms (e.g., Slack, Google Workspace, Salesforce, Confluence, Jira).
• Excellent executive communication skills with a proven ability to present technical strategies, tradeoffs, and results to C-suite stakeholders with clarity and confidence.
• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field. Master’s degree or equivalent practical experience preferred.

Nice To Haves

• Knowledge-Driven AI Systems: Experience building systems where AI operates on structured organizational knowledge (knowledge graphs, ontologies, semantic models) rather than unstructured document search alone. Understanding of how to make AI truly understand organizational context.
• Model Context Protocol (MCP): Hands-on experience building or integrating MCP servers to connect AI agents with enterprise data sources and tools.
• Multi-Agent Systems: Experience designing multi-agent architectures where specialized agents collaborate on complex tasks (e.g., research agent + drafting agent + review agent).
• Vector Databases & RAG Pipelines: Experience with vector stores (Pinecone, Weaviate, ChromaDB, DuckDB vss, Databricks) and building retrieval-augmented generation pipelines for enterprise knowledge bases.
• Team Building & People Leadership: Experience recruiting, mentoring, and leading technical teams.
• Product Thinking: Ability to think about internal tools as products with users, adoption curves, feedback loops, and iteration cycles. Experience partnering with Product organizations to translate internal capabilities into customer-facing features.
• Cloud Platforms: Experience with AWS, GCP, or Azure for deploying and scaling AI applications, including containerized services and serverless functions.
• Enterprise Data Tools: Familiarity with Databricks, Airflow, Redshift, Amplitude, Apache Superset, or similar systems.
• Aviation Industry: Experience in aviation, aerospace, or similarly regulated industries is a plus but not required.

Responsibilities

• Architect and build an enterprise knowledge graph platform that captures, structures, and connects organizational knowledge across functions, projects, decisions, and people.
• Design the pipelines and integration architecture that allows the platform to consume information from diverse sources (meetings, documents, communications, operational systems) and maintain a living, queryable representation of how the organization operates.
• Build and maintain MCP servers and connectors to integrate the knowledge platform with enterprise systems including Slack, Google Workspace (Gmail, Calendar, Drive), Confluence, Tableau, Salesforce, Databricks, Jira, and internal APIs.
• Implement scalable retrieval, contextualization, and synthesis capabilities so that AI agents can traverse organizational knowledge to answer complex, cross-functional questions and automate multi-step workflows.
• Design, build, and deploy custom AI agents using Anthropic’s Claude Agent SDK (Python and/or TypeScript) and complementary frameworks to automate complex knowledge work across Finance, Revenue Operations, Customer Success, Legal, HR, and Product.
• Create custom Claude Cowork plugins, skills, and workflows that package institutional knowledge and platform capabilities into repeatable, org-specific experiences for non-technical users.
• Implement robust permission models, guardrails, and human-in-the-loop approval workflows to ensure AI agents operate safely within enterprise compliance requirements.
• Design and maintain prompt engineering strategies, system prompts, and configuration frameworks that ensure consistent, high-quality agent behavior across use cases.
• Partner directly with the CEO, CFO, CRO, and other C-suite leaders and their teams to translate ambiguous business needs into well-scoped AI solutions, presenting technical approaches, tradeoffs, and results in executive-ready formats.
• Define and execute a phased rollout strategy: prove the platform with the executive leadership team, extend to their direct reports and functional teams, and ultimately scale to the broader Jeppesen ForeFlight workforce.
• Build the business case for and grow an internal AI products team - recruiting, mentoring, and leading engineers and AI specialists as the function scales from a founding team of one to a full product organization.
• Partner with the Product organization to identify opportunities where internal AI capabilities (knowledge graph, agentic workflows, contextual intelligence) can be translated into customer-facing product features and new revenue streams.
• Evaluate emerging AI frameworks, foundation models, and tooling and make build-vs-buy recommendations to leadership. Maintain a forward-looking technical roadmap for the internal AI platform.
• Establish testing, monitoring, and observability patterns for production systems, including logging, audit trails, and performance benchmarks.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal