Staff AI Engineer, Apollo.io
$200-280k
AWS
GCP
Python
Azure
ChatGPT
Senior and Expert level
Remote from US
Sales intelligence and engagement platform
Be an early applicant
Sales intelligence and engagement platform
1001+ employees
B2BLead generationAnalyticsBusiness IntelligenceSaaSAPIAutomationSales
Be an early applicant
$200-280k
AWS
GCP
Python
Azure
ChatGPT
Senior and Expert level
Remote from US
1001+ employees
B2BLead generationAnalyticsBusiness IntelligenceSaaSAPIAutomationSales
Company mission
To build the future of go-to-market solutions.
Role
Who you are
- 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
- You've built AI systems that real users depend on, not just demos or research projects
- You understand the difference between a working prototype and a production-ready system
- You have experience with user feedback, iterative improvements, and feedback systems
- You can design end-to-end systems, including back-end systems, asynchronous workflows, LLMs, and agentic systems
- You understand the cost-benefit trade-offs of different AI approaches
- You've made decisions about when to use different LLM providers, fine-tuning vs prompting, and architecture choices
- You implement repeatable, quantifiable evaluation methodologies
- You track performance across iterations and can explain what makes systems successful
- You prioritize safety, reliability, and user experience alongside capability
- You stay current with the rapidly evolving LLM landscape
- You can quickly adapt to new models, frameworks, and techniques
- You're comfortable working in ambiguous problem spaces and breaking down complex challenges
What the job involves
- As a Staff AI Engineer on our AI Engineering team, you will be responsible for building and productionizing advanced AI systems powered by Large Language Models (LLMs) and intelligent agents
- You'll work on critical Apollo capabilities including our AI Assistant, Autonomous AI Agents, Deep Research Agents, Conversational Assistant, Semantic Search, Search Personalization, and AI Power Automation features that directly impact millions of users' productivity
- Agent Architecture & Implementation: Build sophisticated multi-agent systems that can reason, plan, and execute complex sales workflows
- Context Management: Develop systems that maintain conversational context across complex multi-turn interactions
- LLM and Agentic Platforms: Build scalable large language model and agentic platforms that enable widespread adoption and viability of agent development within the Apollo ecosystem
- Backend Systems: Build back-end systems necessary to support the agents
- AI features: Conversational AI, Natural Language Search, Personalized Email Generation and similar AI features
- Search Scoring & Ranking: Develop and improve recommendation systems and search relevance algorithms
- Entity Extraction: Build models for automatic company keywords, people keywords, and industry classification
- Lookalike & Recommendation Systems: Create intelligent matching and suggestion engines
- Design and Deploy Production LLM Systems: Build scalable, reliable AI systems that serve millions of users with high availability and performance requirements
- Agent Development: Create sophisticated AI agents that can chain multiple LLM calls, integrate with external APIs, and maintain state across complex workflows
- Prompt Engineering Excellence: Develop and optimize prompting strategies, understand trade-offs between prompt engineering vs fine-tuning, and implement advanced prompting techniques
- System Integration: Build robust APIs and integrate AI capabilities with existing Apollo infrastructure and external services
- Evaluation & Quality Assurance: Implement comprehensive evaluation frameworks, A/B testing, and monitoring systems to ensure AI systems meet accuracy, safety, and reliability standards
- Performance Optimization: Optimize for cost, latency, and scalability across different LLM providers and deployment scenarios
- Cross-functional Collaboration: Work closely with product teams, backend engineers, and stakeholders to translate business requirements into technical AI solutions
Our take
Apollo's sales intelligence and engagement platform integrates with companies’ existing internal tools, such as LinkedIn, Salesforce and Hubspot, to increase and optimize sales and marketing leads. Rather than simply employing a volume-heavy approach to leads, Apollo’s software allows users to focus on more convertible prospects, while automating task management and workflow.
The company launched in 2015 and grew steadily in its early years, but the period since 2021 has seen it enter a rapid scale up. Now its customer base includes the likes of Autodesk, Stripe, Docusign and Yelp.
Apollo now intends to keep the upward momentum going, having secured major funding in mid-2023 and is also investing heavily in India as its R&D center, where there’s a burgeoning pool of tech talent. In early 2023, Apollo reported record revenue numbers and appointed a new CPO, indicating a solidification of these aims.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Top investors
75% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Aug 2023
$100m
SERIES D
Mar 2022
$110m
SERIES C
Total funding: $251.4m
Company benefits
- Remote first
- Great compensation package and culture
Company HQ
SoMa, San Francisco, CA
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