Software Engineer, AI

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Calabrio, Inc.

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2007

🏢 Enterprise

☁️ SaaS

🤖 Artificial Intelligence

Enterprise • SaaS • Artificial Intelligence

Calabrio, Inc. is a provider of workforce engagement management (WEM) solutions, offering a fully integrated cloud-based suite known as Calabrio ONE. The company focuses on optimizing contact centers by combining tools for workforce management, quality management, call recording, analytics, and AI-driven insights to boost performance and customer engagement. Calabrio ONE is designed to empower agents through automated scheduling and forecasting while enhancing customer experiences with personalized coaching and performance insights. The platform is used across a variety of industries, helping to build brand trust and improve business intelligence with its AI-fueled analytics solutions.

📋 Description

• Design AI systems • Build end-to-end AI solutions using machine learning, deep learning, NLP, and generative AI technologies. • Develop LLM-powered applications • Create applications using foundation models, prompt engineering, retrieval-augmented generation, structured outputs, function/tool calling, and agent workflows. • Build agentic AI solutions • Design and implement AI agents that can plan, reason through multi-step tasks, interact with external tools and APIs, retrieve relevant context, and execute actions within controlled business processes. • Develop multi-agent and orchestration workflows • Create orchestrated AI systems where multiple agents or components collaborate to solve complex tasks, with clear control flow, observability, and fallback handling. • Productionize models and AI agents • Deploy, monitor, and maintain AI/ML models and agentic systems in production environments with strong reliability, performance, and safety standards. • Build data and inference pipelines • Develop pipelines for ingestion, preprocessing, vector search, model inference, agent memory/context management. • Improve quality and evaluation • Define offline and online evaluation frameworks for model quality, latency, safety, task completion, agent reliability, and business outcomes. • Optimize performance and cost • Improve model selection, prompt efficiency, agent orchestration, latency, throughput, caching, token usage, and serving efficiency. • Ensure governance and safety • Apply best practices for security, privacy, responsible AI, model risk controls, guardrails, agent permissions, compliance, and human-in-the-loop review where needed.

🎯 Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field required. Master’s degree preferred. • 3+ years of end-to-end experience training, evaluating, testing, deploying, and monitoring machine learning models in production. • Hands-on experience building applications with LLMs, prompt engineering, retrieval-augmented generation, structured outputs, and model evaluation. • Experience with frameworks or platforms for LLM and agent orchestration, such as LangChain, LangGraph, Strands AI, or equivalent architectures. • Experience designing or building AI agents that use planning, memory, tool calling, workflow orchestration, agent-to-agent and external system integration to complete multi-step tasks. • Strong experience with Python and backend frameworks such as Flask or Django for building production APIs and AI services. • Strong understanding of machine learning fundamentals and practical experience with NLP tasks such as text classification, NER, clustering, topic modeling, semantic search, and conversational AI. • Experience with fine-tuning LLMs and transformer-based models such as BERT, RoBERTa, ALBERT, and a solid understanding of tokenizers, embeddings, pre-trained models, and adaptation techniques. • Experience with SQL and NoSQL databases, vector databases or embedding stores, and data pipelines for AI applications. • Experience with model serving, observability, evaluation, error analysis, prompt/version management, and monitoring of AI systems in production. • Familiarity with Linux systems and standard software engineering practices including testing, CI/CD, APIs, and version control. • Nice to have: • Experience with AWS, Azure, or GCP • Experience with Docker and Kubernetes • Experience with ETL and Data Engineering projects • Experience with PostgreSQL, Snowflake, or MongoDB • Experience with Kubeflow, or Airflow

🏖️ Benefits

• Global team recognized for their passion and innovation • Innovative product culture and project exposure • Training and development from industry-leading experts • Cutting edge benefit programs that include: medical and dental insurance, disability and life insurance, flexible PTO, paid holidays and parental leave, and more • We offer market competitive pay and benefits based upon the candidate’s skills, experience, and qualifications. Starting rate of pay for this salaried position is targeted at $90,000.