Director of AI Engineering

Apollo.io is the leading go-to-market solution for revenue teams, trusted by over 500,000 companies and millions of users globally. Founded in 2015 and valued at $1.6 B, Apollo provides sales and marketing teams with verified contact data for over 210 million B2B contacts and automates the outreach process, turning prospects into customers.

We are entering a hyper‑growth phase of AI innovation and are hiring a Director of AI Engineering to lead the strategy, engineering execution, and cross‑functional integration of Apollo’s applied AI systems.

As the Director of AI Engineering, you will own the end‑to‑end delivery of Apollo’s AI roadmap spanning autonomous agentic systems, LLM‑powered workflows, search & relevance, personalization, and production‑grade ML infrastructure. You will lead and scale a high‑impact AI Engineering organization responsible for turning cutting‑edge AI techniques into real, revenue‑driving product capabilities used by millions.

This role sits at the intersection of Engineering, Product, Machine Learning, Growth, and GTM
, requiring deep technical leadership, exceptional product intuition, and a track record of shipping AI systems that create measurable business outcomes.

• Define the multi‑year technical vision for Apollo’s AI stack, spanning agents, orchestration, inference, retrieval, and platformization.
• Prioritize high‑impact AI investments by partnering with Product, Design, Research, and Data leaders to align engineering outcomes with business goals.
• Establish technical standards, evaluation criteria, and success metrics for every AI‑powered feature shipped.

• Lead the architecture and deployment of long‑horizon autonomous agents
  , multi‑agent workflows, and API‑driven orchestration frameworks.
• Build reusable, scalable agentic components that power GTM workflows like research, enrichment, sequencing, lead scoring, routing, and personalization.
• Own the evolution of Apollo’s internal LLM platform for high‑scale, low‑latency, cost‑optimised inference.

• Oversee model‑driven experiences for natural‑language interfaces, RAG pipelines, semantic search, personalised recommendations, and email intelligence.
• Partner with Product & Design to build intuitive conversational UX that hides underlying complexity while elevating user productivity.
• Implement rigorous evaluation frameworks, including offline benchmarking, human‑in‑the‑loop review, and online A/B experimentation.
• Ensure robust observability, monitoring, and safety guardrails for all AI systems in production.
• Drive continuous model improvement through telemetry, feedback loops, and data‑driven performance tuning.

• Build and lead a world‑class AI Engineering team of senior ICs, managers, and cross‑functional collaborators.
• Foster a culture of experimentation, velocity, and pragmatic engineering, where speed and safety coexist.
• Mentor engineers on system design, LLM architectures, distributed systems, and applied ML best practices.
• Upskill the broader engineering org in AI‑native development, tooling, and automation.

• Collaborate closely with Data Science, Product, Design, and Research teams to ensure AI capabilities integrate seamlessly into the GTM user journey.
• Accelerate learning cycles by combining LLM experimentation, product iteration, telemetry insights, and engineering automation.

• 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 (Lang Chain, Llama Index), 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 optimisations.
• Demonstrated ability to lead…