Principal AI Engineer

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August 18

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Apollo.io

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B2B • SaaS • Artificial Intelligence

Apollo. io is an all-in-one sales platform designed to streamline and enhance sales operations from lead generation to deal management. The platform offers tools for contact and account search, scores and signals analysis, inbound optimization, sales engagement, and more, leveraging AI and a living data network for comprehensive sales intelligence. Apollo. io is ideal for sales professionals, marketers, and revenue operations teams aiming to enhance productivity and efficiency by automating workflow tasks and integrating CRM systems. With a focus on improving sales performance through analytics and conversation intelligence, Apollo. io helps businesses find the right leads at the right time, nurture those leads effectively, and close deals efficiently.

51 - 200 employees

Founded 2015

🤝 B2B

☁️ SaaS

🤖 Artificial Intelligence

📋 Description

• End-to-End Agentic Systems: • 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.

🎯 Requirements

• 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.). • 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. • 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. • 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.