Principal AI Engineer

Purpose:

Athene’s Future Engineer Initiative is reimagining the software development lifecycle in the age of AI. We are building the foundation for agentic software engineering — where intelligent systems, model context protocols (MCPs), and developers collaborate to deliver secure, high-quality software faster and more reliably.

We are seeking a Principal AI Engineer to contribute to the design and implementation of this transformation. This role will work alongside other senior engineers, architects, and AI specialists to engineer the AI-augmented SDLC platform and embed intelligent automation into every stage of development. Your deep technical expertise and comprehensive understanding of industry-leading practices will guide and empower our engineering teams to deliver exceptional software solutions.

Accountabilities:

• Contribute to the design and evolution of the AI-augmented SDLC platform: help architect and implement the next-generation developer experience integrating AI agents, MCPs, and automation across build, test, review, and release pipelines.

• Operationalize AI engineering best practices: establish frameworks for RAG, vector search, and model evaluation; define standards for prompt engineering, versioning, and observability.

• Engineer for reliability and scale: ensure systems are extensible, testable, and compliant, embedding best practices from DORA’s AI Capabilities Model (healthy data ecosystems, small batches, strong version control).

• Lead by doing, embed with engineering teams to help implement AI-native workflows; provide mentorship and technical guidance to accelerate organizational adoption.

• Build agents and skills to assist with all aspects of software development — from architecture and code generation to deployment automation, testing, and operational diagnostics.

• Integrate AI capabilities into Athene’s Developer Portal to provide engineers with seamless access to intelligent tools, agents, and automation directly within their daily workflows.

• Collaborate across software, platform, and product teams to establish and maintain best practices in areas such as unit testing, branching strategies, architecture, cloud-native patterns, DevOps, and AI adoption.

Qualifications and Experience:

• Bachelor’s degree or equivalent experience with 6+ years in software, platform, or systems engineering, including hands-on experience with Generative or Agentic AI systems.

• Proven success designing and operating large-scale, cloud-native developer platforms or toolchains that improve engineering velocity, reliability, and compliance.

• Strong expertise in modern SDLCs and software architecture, with proficiency in Python, TypeScript/Node.js, and AWS or Azure environments.

• Demonstrated experience integrating AI assistants and agentic workflows into the SDLC (e.g., code generation/review, testing, CI/CD, deployment), using LLM and agent frameworks such as LangChain, AutoGen, LlamaIndex, LangGraph, or equivalent.

• Ability to define and enforce engineering standards, metrics, and responsible AI practices, while mentoring engineers and collaborating across teams to deliver scalable, systemic improvements.