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, from rapidly growing startups to some of the world's largest enterprises. Founded in 2015, the company is one of the fastest growing companies in SaaS, raising approximately $250 million to date and valued at $1.6 billion. Apollo.io

provides sales and marketing teams with easy access to verified contact data for over 210 million B2B contacts and 35 million companies worldwide, along with tools to engage and convert these contacts in one unified platform. By helping revenue professionals find the most accurate contact information and automating the outreach process, Apollo.io

turns prospects into customers.Apollo raised a series D in 2023 and is backed by top-tier investors, including Sequoia Capital, Bain Capital Ventures, and more, and counts the former President and COO of Hubspot, JD Sherman, among its board members.

Apollo.io is the AI-native GTM platform used by millions of professionals worldwide, helping revenue teams automate workflows, personalize outreach, and convert prospects into customers. Backed by Sequoia and Bain Capital and valued at $1.6B+, Apollo is one of the fastest-growing SaaS companies in the world, shipping AI-first capabilities across assistants, agentic automation, search, and generation at massive scale.

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.

Your Role & Mission

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.

You will define the long-term architecture for agentic AI at Apollo, elevate engineering excellence, mentor senior ICs and managers, and accelerate Apollo’s position as the AI-native leader in the go-to-market ecosystem.

What You’ll Own & Deliver

AI Systems Strategy & Roadmap

• 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.

Agentic Systems & Applied AI Delivery

• 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-optimized inference.

AI Assistants, Search & Personalization

• Oversee model-driven experiences for natural-language interfaces, RAG pipelines, semantic search, personalized recommendations, and email intelligence.
• Partner with Product & Design to build intuitive conversational UX that hides underlying complexity while elevating user productivity.

Experimentation, Evaluation & Observability

• 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.

Technical Leadership & Team Building

• 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.

Cross-Functional Impact & Execution Excellence

• 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.

What We’re Looking For

Technical & Production Expertise

• 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.

Leadership, Strategy & Delivery

• Demonstrated ability to lead senior engineers, define technical roadmaps, and deliver outcomes aligned to business metrics.
• Experience building or scaling teams working on experimentation, optimization, personalization, or ML-powered growth systems.
• Exceptional ability to simplify complex problems, set clear standards, and drive alignment across Product, Data, Design, and Engineering.
• Strong product sense, ability to weigh novelty vs. impact, focus on user value, and prioritize speed with guardrails.

AI-Native Engineering Mindset

• Fluent in integrating AI tools into engineering workflows for code generation, debugging, delivery velocity, and operational efficiency.
• Comfortable balancing rapid experimentation with production rigor, ensuring features are safe, reliable, and measurable.
• Thrives in an environment where learning velocity, automation, and continuous improvement are core values.

What Will Make You Successful at Apollo

• You raise the bar on engineering leadership — setting standards that elevate execution, quality, and innovation across the org.
• You operate with ownership and urgency. Apollo ships fast, iterates fast, and expects leaders to turn ambiguity into scalable systems.
• You connect AI research to real product outcomes. Novelty matters less than moving business metrics materially.
• You excel cross-functionally. You influence Product, Desig, and Data with clarity, technical depth, and pragmatic decision-making.
• You thrive in AI-native environments. You use AI daily to accelerate engineering, improve workflows, and teach your teams to do the same.

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