ML Engineer II

Role Description
We are looking for senior, autonomous software engineers to build AI-powered product features for a Contact Center as a Service (CCaaS) platform. This role sits at the intersection of product engineering, AI systems, and scalable cloud architecture. You will design, build, and evolve AI-based capabilities such as: Real-time and post-call transcription services LLM- features (summarization, agent assist, analytics, automation) Prompt management and orchestration Retrieval-Augmented Generation (RAG) pipelines Knowledge base ingestion and management AI-driven workflows embedded directly into CCaaS user experiences You are expected to deeply understand product requirements, make technical decisions independently, and contribute end-to-end from architecture and backend services to frontend experiences. What You ll Do AI-Centric Product Development Design and implement AI-based product features for CCaaS use cases Integrate LLM services, transcription engines, embeddings, vector databases, and RAG pipelines Design prompt strategies, prompt versioning, and evaluation mechanisms for reliable AI behavior. Build systems that safely and efficiently interact with external AI providers (OpenAI, Azure OpenAI, AWS, etc.). Architecture & Scalability Design scalable, modular, and observable AI architectures suitable for real-time and high-volume CCaaS workloads. Apply best practices for event-driven, asynchronous, and distributed systems. Ensure AI systems are cost-aware, fault-tolerant, and designed for continuous evolution. Collaborate on decisions around data flow, latency, throughput, and reliability especially for real-time voice and messaging scenarios. Full-Stack Ownership Build and maintain backend services using Node.js, TypeScript, and NestJS. Develop frontend experiences using React.js (or similar), especially for AI-assisted workflows and real-time UI updates. Contribute to API design, frontend-backend contracts, and system integrations. For frontend-leaning roles: focus on AI-driven UX, real-time dashboards, agent tools, and explainability of AI outputs. Product & Team Collaboration Work closely with product managers, designers, QA, and other engineers from discovery to delivery. Translate business and product needs into clear technical designs and implementation plans. Actively challenge assumptions and propose better solutions technically and from a product perspective. Mentor peers and contribute to engineering best practices and standards. Engineering Excellence Write clean, maintainable, well-tested code. Build automated tests for business-critical and AI-dependent logic. Participate in code reviews and architectural discussions. Create and maintain technical documentation for both systems and AI behaviors. Continuously improve system performance, reliability, and developer experience. What You Bring Bachelor s degree in Computer Science or equivalent practical experience. 6 - 8 years of professional software development experience. Strong experience with Node.js, TypeScript, NestJS, and React.js (or equivalent frontend frameworks). Proven ability to work autonomously, owning features from concept to production. Solid understanding of loosely coupled, modular, and event-driven architectures. Hands-on experience building AI-powered production features (not just experimentation). LLM concepts and limitations Prompt engineering and prompt lifecycle management RAG architectures and vector search Knowledge base ingestion and enrichment pipelines Experience integrating with AI services (e.g., OpenAI, Azure OpenAI, AWS Bedrock, or similar). Ability to reason about latency, accuracy, cost, and reliability trade-offs in AI systems. Experience with Docker and Kubernetes. Familiarity with cloud-native architectures (AWS, Azure). Experience with message brokers / streaming platforms (e.g., Apache Kafka). Strong Git workflows and CI/CD best practices. Comfort working in Linux-based environments. Mindset & Soft Skills Product-oriented mindset: you understand why you rebuilding something, not just how. Strong analytical and critical thinking skills. Excellent communication skills; comfortable working with distributed teams (fluent English required). Willingness to challenge ideas constructively and propose alternatives. Passion for learning, experimentation, and staying current with AI and software trends. Leadership mindset whether through mentoring, technical guidance, or ownership. Additional Requirements We Consider Essential Knowledge of VoIP, real-time communications, or contact center platforms. Experience handling real-time or near-real-time data streams. Understanding of observability for distributed and AI-driven systems. Awareness of AI governance, security, and privacy considerations, especially when handling customer conversations and data. Strong bias toward simple, maintainable solutions over over-engineering.
Skills
React, Node.js, AI Governance, CCaaS

Work arrangement
No