Software Engineer

Summary

Join Kustomer, a leading conversational CRM platform, as an AI Platform Engineer to architect and build the next generation of our agentic customer service platform. This role blends AI systems engineering, distributed computing, and semantic data processing, focusing on developing autonomous AI agents, intelligent tool integrations, and the observability infrastructure. You will drive the development of autonomous AI agents, design and implement agentic systems, and build observability and evaluation frameworks. The ideal candidate possesses deep understanding of agentic architectures, modern AI frameworks, and the ability to envision and implement the future of human-AI collaborative systems. Kustomer offers a collaborative environment, remote-friendly work options, and a commitment to professional growth. The company is growing rapidly and seeks individuals passionate about AI and automation.

Requirements

• 7+ years of software engineering experience with 3+ years focused on AI/ML applications and data-intensive systems
• Expertise in AI/ML frameworks including experience with LLMs, transformer architectures, and agent orchestration platforms (LangGraph, AutoGen, CrewAI, or similar)
• Experience with foundational model providers including OpenAI, Anthropic, and AWS Bedrock for production AI applications
• Strong background in data engineering with expertise in vector databases, semantic search, RAG architectures, and real-time data processing
• Distributed systems expertise including message queues, event-driven architectures, microservices, and cloud-native computing
• Applied ML/NLP experience with hands-on work in information retrieval, natural language understanding, and knowledge representation
• Programming proficiency in TypeScript/Node.js and Go (preferred for AI systems and applications) with Python experience for AI/ML modeling, tuning, evaluation and verification work
• Strong database and big data expertise across multiple paradigms, including: SQL, Document, Graph, OLAP, NoSQL, Vector databases, and/or Search engines
• Production AI system experience including model deployment, monitoring, A/B testing, and performance optimization
• Understanding of agentic system principles including autonomy, goal-oriented behavior, tool integration, and multi-agent collaboration
• Cloud platform expertise particularly AWS services for AI/ML workloads (SageMaker, Bedrock, Lambda, etc.)

Responsibilities

• Design and implement agentic systems spanning our three core focus areas: AI Engine architecture, Tools & Integrations, and Configuration & Observability
• Build autonomous AI agents with sophisticated reasoning capabilities, agent-to-agent communication protocols, and hierarchical orchestration patterns
• Develop semantic data pipelines for information retrieval, embedding generation, knowledge graph construction, and real-time context synthesis
• Architect tool integration ecosystems using Model Context Protocol (MCP) and function calling frameworks to enable agent-system interactions
• Implement distributed AI workflows managing agent lifecycles, long-term memory systems, and multi-agent collaboration patterns
• Build observability and evaluation frameworks for monitoring agent behavior, measuring AI system performance, and ensuring reliability
• Design machine-first APIs optimized for agent consumption while maintaining human accessibility through complementary interfaces
• Apply reinforcement learning techniques including RLHF for agent alignment and continuous improvement of autonomous systems
• Collaborate across technical domains to translate AI platform requirements into production-ready capabilities
• Drive innovation in agentic architectures by staying current with developments in transformer models, reasoning frameworks, and multi-agent systems

Preferred Qualifications

• Experience with semantic web technologies including knowledge graphs, ontologies, and linked data systems
• Familiarity with modern AI agent frameworks and understanding of the evolving agent ecosystem
• Background in reinforcement learning and human feedback integration for AI alignment
• Experience with real-time AI systems requiring low-latency inference and streaming data processing
• Understanding of AI safety and governance principles for autonomous system deployment
• Knowledge of emerging AI protocols like MCP and experience building extensible AI applications
• Contributions to AI/ML open source projects demonstrating applied AI platform development (bonus)
• Frontend development experience with React and modern web technologies (bonus, not required)

Benefits

• 100% healthcare coverage
• 401K
• WiFi and Mobile reimbursement
• Generous vacation policy
• Pension
• Supplemental health insurance
• Other perks