Software Engineer, AI

Calabrio • Toronto, ON

12h

About The Position

Calabrio-Verint is seeking a highly skilled and experienced Software Engineer, AI to play a key role in their digital transformation program. This role involves designing, building, deploying, and optimizing AI-powered products and platforms, with a strong focus on LLM applications, agentic AI systems, applied machine learning, backend engineering, data pipelines, evaluation, and production operations. The goal is to turn AI capabilities into reliable, scalable, measurable, secure, and maintainable business solutions. The ideal candidate can move beyond experimentation to deliver production-grade AI systems, including autonomous and semi-autonomous AI agents capable of reasoning, planning, using tools, retrieving knowledge, and taking actions safely within defined business workflows. Calabrio is committed to establishing a value fabric that transforms customer, employee, and stakeholder experiences through seamless, integrated, agile, data-driven, and secure Digital Services.

Requirements

• Problem solver - devise and implement advanced NLP algorithms and LLM models to address intricate challenges in Conversation Intelligence analytics
• Strong team player – works with internal and external stakeholders to solve problems and actively incorporate input from various sources
• Excellent communication skills and collaborative working style
• Ability to think “out of the box”, strong critical thinking and analytical skills
• 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 Haves

• 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

Responsibilities

• Design AI systems
• Build end-to-end AI solutions using machine learning, deep learning, NLP, and generative AI technologies.
• Develop LLM-powered applications using foundation models, prompt engineering, retrieval-augmented generation, structured outputs, function/tool calling, and agent workflows.
• Build agentic AI solutions by designing and implementing 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 where multiple agents or components collaborate to solve complex tasks, with clear control flow, observability, and fallback handling.
• Productionize models and AI agents by deploying, monitoring, and maintaining AI/ML models and agentic systems in production environments with strong reliability, performance, and safety standards.
• Build data and inference pipelines for ingestion, preprocessing, vector search, model inference, agent memory/context management.
• Improve quality and evaluation by defining offline and online evaluation frameworks for model quality, latency, safety, task completion, agent reliability, and business outcomes.
• Optimize performance and cost by improving model selection, prompt efficiency, agent orchestration, latency, throughput, caching, token usage, and serving efficiency.
• Ensure governance and safety by applying best practices for security, privacy, responsible AI, model risk controls, guardrails, agent permissions, compliance, and human-in-the-loop review where needed.

Benefits

• Global team recognized for their passion and innovation
• Innovative product culture and project exposure
• Training and development from industry-leading experts
• Medical and dental insurance
• Disability and life insurance
• Flexible PTO
• Paid holidays
• Parental leave
• Market competitive pay and benefits based upon the candidate’s skills, experience, and qualifications.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior