Senior AI Engineer at Apollo.io

, , India -

Full Time

Start Date

Immediate

Expiry Date

11 May, 26

Salary

0.0

Posted On

10 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Engineering, Large Language Models, Python, Backend Engineering, API Integration, Prompt Engineering, Agent Development, Production Deployment, Quality Assurance, Data Pipeline Management, A/B Testing, Monitoring, Evaluation Frameworks, Scalable Systems, Conversational AI, Natural Language Processing

Industry

Software Development

Description

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. Your Role & Mission As a Senior 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. The mission of our AI teams is to leverage Apollo's massive scale data and cutting-edge AI to understand and predict user behaviors, personalize experiences, and optimize every stage of the customer journey through intelligent automation. What You'll Be Working On AI Assistant & Agent Systems 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 Classical AI/ML (Optional Focus) 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 Key Responsibilities 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 Required Qualifications Core AI/LLM Experience (Must-Have) 7+ 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 Technical Engineering Skills 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) Quality & Evaluation Focus 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 What Makes a Great Candidate Production-First Mindset 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 Technical Depth with Business Impact 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 Evaluation & Quality Excellence 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 Adaptability & Learning 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 Our AI Impact at Apollo Join a team that's already making significant impact: Our AI Assistant helps sales teams automate research, scoring, and outreach processes Assisted Prompting Mode allows users to leverage AI power-ups without being prompt engineering experts Our AI email assistant processes hundreds of thousands of words monthly for Professional plan user We help users "book more meetings in less time by automating research, scoring, outreach, & more with embedded AI sales assistants" If you're looking for a place where your AI engineering work directly impacts millions of users, where you can push the boundaries of what's possible with LLMs and agents, and where your career can thrive in the AI-native future—Apollo is the place for you. Application Instructions To help us identify candidates with strong real-world AI engineering experience, please answer the following five short screening questions directly in your application (2–5 sentences per response). Applications without answers to these questions will not be reviewed. Apollo.io Tech Blog : deep dives into engineering, product design, and company-culture stories from the Apollo team, offering behind-the-scenes insight into how Apollo builds and scales its B2B sales platform We are AI Native Apollo.io is an AI-native company built on a culture of continuous improvement. We’re on the front lines of driving productivity for our customers—and we expect the same mindset from our team. If you're energized by finding smarter, faster ways to get things done using AI and automation, you'll thrive here. 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. That’s why we take extreme ownership of our work, move with focus and urgency, and learn voraciously to stay ahead. We invest deeply in your growth, ensuring you have the resources, support, and autonomy to own your role and make a real impact. Collaboration is at our core—we’re all for one, meaning you’ll have 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!

Responsibilities

As a Senior AI Engineer, you will build and productionize advanced AI systems powered by Large Language Models and intelligent agents. You will work on critical capabilities that directly impact user productivity.