Director of AI Engineering

About the Role

Lead the strategy and execution of Apollo's applied AI systems, driving innovation in autonomous agents, LLM-powered workflows, and production-grade ML infrastructure to shape the future of go-to-market solutions.

Responsibilities

• Define and execute the multi-year technical vision for Apollo’s AI stack, including agents, orchestration, inference, and platformization.
• Lead the architecture and deployment of autonomous agents, multi-agent workflows, and API-driven orchestration frameworks.
• Oversee model-driven experiences for natural-language interfaces, RAG pipelines, semantic search, and personalized recommendations.
• Implement rigorous evaluation frameworks, including offline benchmarking, human-in-the-loop review, and online A/B experimentation.
• Build and lead a world-class AI Engineering team, fostering a culture of experimentation and velocity.

Requirements

• 10–15+ years in software engineering, with significant leadership experience owning AI/ML or applied LLM systems at scale.
• Proven history shipping LLM-powered features, agentic workflows, or AI assistants used by real customers in production.
• Deep understanding of LLM orchestration frameworks (LangChain, LlamaIndex), RAG pipelines, vector search, embeddings, and prompt engineering.
• Expert in backend & distributed systems (Python strongly preferred) and cloud infrastructure (AWS/GCP).
• Strong experience with telemetry, observability, and cost-aware real-time inference optimizations.
• Demonstrated ability to lead senior engineers, define technical roadmaps, and deliver outcomes aligned to business metrics.
• Exceptional ability to simplify complex problems, set clear standards, and drive alignment across Product, Data, Design, and Engineering.

Nice-to-Haves

• Experience building or scaling teams working on experimentation, optimization, personalization, or ML-powered growth systems.
• Strong product sense, ability to weigh novelty vs. impact, focus on user value, and prioritize speed with guardrails.
• Fluent in integrating AI tools into engineering workflows for code generation, debugging, delivery velocity, and operational efficiency.