Lead Engineer

Job Description About Us HighLevel is an AI powered, all-in-one white-label sales & marketing platform that empowers agencies, entrepreneurs, and businesses to elevate their digital presence and drive growth. We are proud to support a global and growing community of over 2 million businesses, comprised of agencies, consultants, and businesses of all sizes and industries. HighLevel empowers users with all the tools needed to capture, nurture, and close new leads into repeat customers. As of mid 2025, HighLevel processes over 4 billion API hits and handles more than 2.5 billion message events every day. Our platform manages over 470 terabytes of data distributed across five databases, operates with a network of over 250 microservices, and supports over 1 million hostnames. Our People With over 1,500 team members across 15+ countries, we operate in a global, remote-first environment. We are building more than software; we are building a global community rooted in creativity, collaboration, and impact. We take pride in cultivating a culture where innovation thrives, ideas are celebrated, and people come first, no matter where they call home. Our Impact As of mid 2025, our platform powers over 1.5 billion messages, helps generate over 200 million leads, and facilitates over 20 million conversations for the more than 2 million businesses we serve each month. Behind those numbers are real people growing their companies, connecting with customers, and making their mark - and we get to help make that happen. About The Role We're looking for a lead-level engineer to own and drive Gen AI initiatives for Workflows designing, building, and scaling AI-powered workflow automation features end-to-end. You'll integrate and orchestrate LLMs (OpenAI, Anthropic, Claude, LLaMA, Mistral), design RAG pipelines with vector DBs (Pinecone, Weaviate, FAISS, Qdrant), and implement agentic AI workflows using LangChain, LangGraph, and AutoGen.You'll lead the technical strategy for AI in workflows from prompt engineering and fine-tuning (LoRA, QLoRA, PEFT) to EVAL frameworks that ensure performance, accuracy, and reliability. Our stack: Vue, Node.js, MongoDB, Firestore, ElasticSearch, Redis, all on GCP and we expect you to move seamlessly across it while delivering scalable, production-grade AI capabilities. Requirements: - Leadership & Ownership: Proven experience leading projects and mentoring engineers - Fullstack Engineering: Node.js backend, Vue frontend, API design & scaling - LLM APIs: OpenAI, Anthropic, Bedrock, Claude, LLaMA, Mistral, LlamaIndex - Prompt Engineering: few-shot, CoT, dynamic context, function/tool calling - RAG Pipelines: embeddings, chunking, hybrid retrieval - Vector DBs: Pinecone, Weaviate, FAISS, Qdrant - Agentic AI: multi-step workflows, tool usage, memory (LangChain, LangGraph, AutoGen) - Fine-Tuning: LoRA, QLoRA, PEFT, embedding-based adaptation - EVALs: hallucination detection, groundedness, BERTScore, BLEU, GPTScore - Data Layer: MongoDB, Firestore, ElasticSearch, Redis - Cloud & Deployment: GCP (preferred), AWS, or Azure; Docker/Kubernetes; CI/CD for AI workloads Responsibilities: - Lead the architecture, development, and deployment of AI-powered workflow automation features - Integrate and orchestrate multiple LLM providers with high reliability - Build and optimize RAG pipelines embeddings, chunking, hybrid retrieval using vector databases - Design and implement agentic AI workflows multi-step reasoning, tool usage, memory leveraging LangChain, LangGraph, AutoGen, or similar - Apply prompt engineering best practices: few-shot, chain-of-thought, dynamic context, function/tool calling - Execute fine-tuning/adaptation workflows LoRA, QLoRA, PEFT, and embedding-based customization - Develop and manage EVAL frameworks hallucination detection, groundedness, BERTScore, BLEU, GPTScore to track and improve model quality - Build robust, scalable Node.js APIs and Vue-based frontends, integrating seamlessly with our stack - Work with MongoDB, Firestore, ElasticSearch, Redis to design efficient data flows for AI workloads - Ensure observability, performance tuning, and cost optimization in GCP-based deployments - Collaborate closely with product, design, and infra teams to deliver high-impact features on time - Mentor engineers, set best practices, and drive technical decision-making in the AI workflows domain EEO Statement: At HighLevel, we value diversity. In fact, we understand it makes our organisation stronger. We are committed to inclusive hiring/promotion practices that evaluate skill sets, abilities, and qualifications without regard to any characteristic unrelated to performing the job at the highest level. Our objective is to foster an environment where really talented employees from all walks of life can be their true and whole selves, cherished and welcomed for their differences while providing excellent service to our clients and learning from one another along the way Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions. #NJ1 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. 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