Job DescriptionCalabrio-Verint is looking for a highly skilled and experienced Software Engineer, AI to perform a key role in our digital transformation program, and deliver exceptional customer experience supported by trusted, and resilient business solutions. As an AI Software Engineer, you will design, build, deploy, and optimize 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. You will turn AI capabilities into reliable business solutions that are scalable, measurable, secure, and maintainable.
Overview of Job Function:This role is ideal for someone who can move beyond experimentation and deliver production-grade AI systems, including autonomous and semi-autonomous AI agents that can reason, plan, use tools, retrieve knowledge, and take actions safely within defined business workflows. Calabrio has embarked journey and is truly committed to establishing a value fabric that transforms its customer, employee, and stakeholder experiences through seamless integrated, agile, data-driven, and secure Digital Services. Such an endeavor requires leaders passionate about customer experience and committed to consistently delivering value while focusing on digital services with inherent trust and resilience.
We're looking for: - 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
Principal Duties and Essential Responsibilities:- 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.
Minimum Requirements:- Bachelor's degree in Computer Science, Engineering, or a related field required. Master's degree preferred.
- 5+ 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.
Preferred Skills:- 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
About the Team 
