Apollo.io
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.
Staff AI Engineer
Job not on LinkedIn
August 22
Apollo.io
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.
📋 Description
• Staff AI Engineer on Apollo.io's AI Engineering team responsible for building and productionizing advanced AI systems powered by LLMs and intelligent agents. • You’ll work on AI capabilities including AI Assistant, Autonomous AI Agents, Deep Research Agents, Conversational Assistant, Semantic Search, and AI Power Automation • Goal: leverage Apollo's data to understand user behaviors, personalize experiences, and optimize customer journeys via intelligent automation • Design and Deploy Production LLM Systems; Agent Development; Prompt Engineering Excellence; System Integration; Evaluation & Quality Assurance; Performance Optimization; Cross-functional Collaboration • Required Qualifications: 8+ years of software engineering with focus on production systems; 1.5+ years of hands-on LLM experience; Production LLM Applications; Agent Development; Prompt Engineering • Technical Engineering Skills: Python, Backend Engineering, LangChain or similar frameworks, API Integration, Production Deployment • Quality & Evaluation Focus: Testing & Evaluation; A/B Testing; Monitoring & Reliability; Data Pipeline Management • Working at Apollo: remote-first, autonomous, growth-focused culture
🎯 Requirements
• 8+ years of software engineering experience with a focus on production systems • 1.5+ years of hands-on LLM experience (2023-present) building real applications with GPT, Claude, Llama, or other modern LLMs • Production LLM Applications: Demonstrated experience building customer-facing, scalable LLM-powered products with real user usage (not just POCs or internal tools) • Agent Development: Experience building multi-step AI agents, LLM chaining, and complex workflow automation • Prompt Engineering Expertise: Deep understanding of prompting strategies, few-shot learning, chain-of-thought reasoning, and prompt optimization techniques • Python Proficiency: Expert-level Python skills for production AI systems • Backend Engineering: Strong experience building scalable backend systems, APIs, and distributed architectures • LangChain or Similar Frameworks: Experience with LangChain, LlamaIndex, or other LLM application frameworks • API Integration: Proven ability to integrate multiple APIs and services to create advanced AI capabilities • Production Deployment: Experience deploying and managing AI models in cloud environments (AWS, GCP, Azure) • Testing & Evaluation: Experience implementing rigorous evaluation frameworks for LLM systems including accuracy, safety, and performance metrics • A/B Testing: Understanding of experimental design for AI system optimization • Monitoring & Reliability: Experience with production monitoring, alerting, and debugging complex AI systems • Data Pipeline Management: Experience building and maintaining scalable data pipelines that power AI systems
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