Principal AI Engineer

Overview 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. Our platform helps sales and marketing teams prospect smarter, automate workflows, and close more deals, all within a unified, AI-native platform. Backed by world-class investors including Sequoia and Bain Capital, Apollo is one of the fastest-growing SaaS companies in the world, valued at $1.6B following our Series D. Why This Role Matters We are entering a new phase of AI-native growth and are looking for a Principal AI Engineer to lead the design and deployment of cutting-edge agentic systems, AI assistants, and LLM-powered features. This role is pivotal to Apollo’s AI roadmap, owning the architecture and productionization of intelligent systems that power the workflows of thousands of GTM teams globally. You’ll be a technical thought leader on the AI Engineering team and work alongside product, backend, and platform leaders to drive forward Apollo’s competitive edge in applied AI. What You’ll Own & Deliver Autonomous AI Agents: Architect and lead the development of multi-agent systems capable of long-horizon planning, reasoning, and API orchestration. Workflow Automation: Build reusable agentic components that integrate deeply into sales and marketing processes. LLM Platformization: Own and evolve our in-house platform for scalable, low-latency, and cost-efficient LLM and agent deployments. AI Assistants and Search Conversational AI & UI: Lead design of interfaces powered by natural language understanding and retrieval-augmented generation (RAG). Semantic & Personalized Search: Build embedding-based, intent-aware search and personalization systems tuned to business user needs. Email Intelligence: Drive innovation in personalized outreach generation using context-aware generation pipelines. Production-Grade Applied AI Latency & Cost Optimization: Tune inference pipelines, caching layers, and model selection logic for high-scale, cost-aware performance. Evaluation at Scale: Define and drive robust offline and online testing methodologies (A/B, sandboxing, human evals) across agents and LLM flows. Feedback Loops: Architect human-in-the-loop systems and telemetry to improve accuracy, UX, and explainability over time. What We’re Looking For Technical & Production Depth: 10+ years of software engineering experience, with at least 3 years in applied LLM or agentic AI systems (2023–present). Proven success in deploying LLM-powered products: Used by real users at scale, not just prototypes or internal tools. Deep backend & systems engineering: Expertise with Python, distributed systems, and scalable APIs. Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks. Experience with RAG pipelines, vector DBs, embedding models, and semantic search tuning. Experience managing performance across cloud providers (e.g., AWS Bedrock, OpenAI, Anthropic, etc.). Agentic Systems & Prompt Engineering Demonstrated experience building multi-step agents, planning workflows, chaining reasoning steps, and integrating APIs with agent memory/state. Comfort with advanced prompting strategies, few-shot and chain-of-thought reasoning, and embedding retrieval setups. Evaluation, Monitoring & CI for AI Strong understanding of AI system evaluation, human ratings, A/B experimentation, and feedback loop pipelines. Experience designing safety-aware, reliable LLM systems in production environments. Experience owning logging, monitoring, and observability for live AI systems. Leadership & Strategic Impact Principal-Level Ownership: You thrive in an ambiguous environment, define company-wide roadmaps, drive the most important Engineering decisions, and mentor others. You lead from the front. AI-Native Mentality: You leverage AI to ship faster and smarter, and champion automation across engineering workflows. Applied Focus: You prioritize impact over novelty. You’re deeply pragmatic in your application of AI research to product features. What Makes This Role Different A Role with Real Autonomy: You’ll own complex systems end-to-end, from LLM prompt design and API orchestration to production deployment and A/B testing at scale. You’re not building demos, you’re shipping critical infrastructure that millions rely on. A Product-First AI Culture: We believe in AI that moves the needle, and your work will directly impact Apollo’s AI Assistants, scoring models, research agents, and automation flows, products that define our differentiation in the market. Compensation & Benefits The listed pay range reflects base salary range, except for sales roles. The range provided is the role’s On Target Earnings (OTE) range, including base salary and targets. Pay ranges may be narrowed during the interview process based on experience, qualifications, and location. Applicants outside the US may request the annual salary range for their location during the interview process. Annual Pay Range $200,000 — $300,000 USD Additional benefits may include equity; 401(k); at least 10 paid holidays per year, flexible PTO, parental leave; wellbeing benefits; life/AD&D/STD/LTD insurance; FSA/HSA and medical, dental, and vision benefits. Why You’ll Love Working at Apollo At Apollo, we’re driven by a shared mission to help our customers unlock their full revenue potential. We take extreme ownership, move with focus and urgency, and learn voraciously to stay ahead. We invest in your growth and provide resources, support, and autonomy to own your role and drive real impact. Collaboration is core—we’re all for one, with a team across departments ready to help you succeed. We encourage bold ideas and courageous action, giving you the freedom to experiment, take smart risks, and drive big wins. If you’re looking for a place where your work matters, where you can push boundaries, and where your career can thrive—Apollo is the place for you. Learn more here #J-18808-Ljbffr