Senior AI Engineer (Conversational AI)

• Design, develop, and maintain production-grade conversational AI systems
• Own AI features from technical design through deployment and production support
• Design scalable AI architectures and agent workflows
• Build and maintain AI evaluation frameworks, benchmarks, and automated testing pipelines
• Continuously improve AI quality through experimentation, evaluation, and data-driven optimization
• Integrate multiple AI providers and select the best models for different use cases
• Monitor production AI systems and proactively improve reliability, quality, and performance
• Collaborate with product, frontend, and backend teams to deliver end-to-end AI features
• Review technical designs and contribute to engineering best practices
• Troubleshoot complex AI and production issues while ensuring high-quality, maintainable solutions
• Stay up to date with the latest advancements in Generative AI and apply them where they create business value

LLM

RAG

Agentic AI

Gen AI

Prompt Engineering

retrieval

OpenAI

Anthropic

Gemini, * 5+ years of experience building AI-powered applications in production

• Experience with conversational AI systems, including voice and/or chat applications
• Experience building AI evaluation frameworks, automated testing pipelines, benchmarking, and regression testing
• Experience integrating multiple AI providers such as OpenAI, Anthropic, Gemini, or similar
• Experience deploying, monitoring, and maintaining AI applications in production environments
• Full-stack development experience with modern backend and frontend technologies
• Experience with cloud platforms, APIs, CI/CD pipelines, and production deployments
• Strong software engineering fundamentals, including clean architecture, design patterns, testing, and maintainable code
• Ability to evaluate multiple AI approaches based on quality, reliability, latency, and cost
• Ability to independently own complex AI projects from design through production with minimal supervision, * Experience building traditional ML applications
• Experience with AI observability, tracing, and monitoring
• Experience mentoring engineers and driving engineering best practices

More Skills

AI system design, context management, memory, multi-agent workflows, reasoning pipelines, AI evaluation frameworks, automated testing pipelines, benchmarking, regression testing, software engineering, clean architecture, design patterns, testing, cloud platforms, APIs, CI/CD pipelines, production deployments, backend technologies, frontend technologies, AI observability, tracing, monitoring, traditional ML applications

• RemoFirst enables global hiring and management through an all-in-one HR platform covering hiring, compliance, payroll, and benefits management
• The company partners with Fortune 500 businesses and leading startups
• Team size is 250+ people and growing
• Early-stage startup environment with autonomy and accountability
• Opportunity to build a tech unicorn
• Direct impact on revenue, customer support, and market differentiation
• Reporting into the Lead AI Engineer
• Competitive compensation
• Culture emphasizes respect, kindness, the right to fail, hard yet smart work, diversity, and inclusion
• Work with colleagues from top tech companies
• Market-leading customers include Microsoft and Mastercard

Prepare for this role

Recommended resources to build the skills for this position. Sponsored.

Generative AI with Large Language Models

Coursera

Comprehensive LLM course covering transformer architecture, fine-tuning, RLHF, and deployment.

Large Language Models: Application through Production

edX

Production-focused LLM course covering deployment, monitoring, and scaling.

Introduction to Generative AI

Coursera

Google Cloud introduction covering Gen AI concepts, model types, and Google AI tools.