Role overview
*Position Title: Senior AI Engineer
Department: Engineering and Product Development
Reports To: Engineering Management
Location: Remote
OnviSource is rapidly expanding its product development and engineering to support its growth in 2026. The company is a high-performing organization with competent, skilled, no-nonsense, results-oriented, and values-centered employees, seeking and hiring only those who match the quality of its current employees.
About OnviSource
OnviSource is a globally recognized innovator in contact center AI and automation solutions**
, delivering
Agentic AI
that blends human expertise with intelligent automation. For over 20 years, OnviSource has empowered contact centers and enterprises to significantly improve the performance of their three most critical functions: agent performance, customer satisfaction, and operational efficiency.
*Position Summary
The Senior AI Engineer will be responsible for researching AI models and technologies, designing, building, and deploying scalable AI solutions based on AI-native architecture to improve call center agent performance, customer experience, and operational efficiency.
The candidate must be highly skilled in Natural Language Processing (NLP), call transcription, speech and interaction analytics, summarization, semantic search, and intelligent automation. The ideal candidate is a hands-on engineer with strong experience building production applications using C#/.NET Core, Python, and JavaScript/TypeScript.
This role requires an experienced, motivated, hardworking, energetic, and coachable senior engineer with a proven track record of successfully delivering complex AI solutions to contact center and enterprise markets, from innovation and architectural designs to product release, deployment, and expansions.
The candidate must also possess an unwavering value system and business integrity.
What we're looking for
Design, develop, and deploy AI-powered applications and services for transcription, summarization, sentiment analysis, search, classification, and workflow automation
Build scalable backend services, APIs, and microservices that integrate AI capabilities into enterprise platforms
Develop and maintain data and model pipelines for transcript processing, retrieval, orchestration, and analytics
Apply LLMs, NLP, and conversational AI techniques to solve business problems in production environments
Build AI, data processing, and model integration workflows using Python
Improve the performance, reliability, security, costs, and scalability of AI services
Provide technical leadership, architectural guidance, and mentoring to other engineers
Design and implement models and pipelines for transcription processing, sentiment analysis, summarization, intent detection, topic extraction, and conversation analytics
Integrate machine learning models and language technologies into call center platforms, quality monitoring tools, and customer experience applications
Collaborate with product, engineering, operations, and business stakeholders to translate contact center challenges into AI-enabled solutions
Improve transcription accuracy, language understanding, and model performance across diverse conversational datasets
Establish best practices for model deployment, monitoring, tuning, and lifecycle management in production environments
Ensure solutions are scalable, secure, maintainable, and aligned with enterprise software engineering standards
Evaluate emerging technologies in NLP, speech recognition, transcription intelligence, and conversational AI for strategic adoption
10+ years of software engineering experience, including production application development
Hands-on experience building and deploying AI, ML, or LLM-powered solutions
Strong proficiency in RESTful APIs, C#/.NET Core, and Python, with experience in JavaScript/TypeScript
Experience with APIs, microservices, distributed systems, and cloud-based deployments
Strong background in natural language processing, language modeling, or conversational AI
Experience working with call transcripts, speech analytics, call center data, or similar interaction data
Familiarity with Agentic AI, model orchestration, evaluation, monitoring, and enterprise integration
Engineering project management, problem-solving, and cross-functional collaboration skills
Minimum 4 years of employment with each past employer
Demonstrable and Proven Success and Track Record
Excellent verbal and written communication skills
High level of business ethics, professionalism, respectful and cordial mannerism, and personal integrity, fully compliant with OnviSource’s core values.
Self-starter, hard-working, providing any amount of work required to get the job done, committed to success, and exceeding performance expectations.
Open to feedback and effectively combining OnviSource’s guidelines with past experiences, continuous learning, and improvement; thriving in the dynamic and challenging environment of OnviSource with its high-level expectations and performance.
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Mathematics, or a related field
What Success Looks Like at OnviSource
Deliver production-ready Native AI capabilities that create measurable customer value
Improve the quality, reliability, and maintainability of Native AI platform features
Reduce latency, cost, and operational risk of AI services in production
Establish engineering best practices for enterprise AI development
Serve as a senior technical contributor and mentor for AI architecture and implementation
Deliver results and demonstrate a high level of business ethics, professionalism, respectful and cordial mannerism, and personal integrity, fully compliant with OnviSource’s core values.
Why Join Us
You will have the opportunity to shape how AI is embedded into mission-critical enterprise workflows, helping build practical, scalable AI solutions that deliver real business outcomes. This role is ideal for engineers who want to grow in their careers, combining a strong software engineering discipline with cutting-edge AI application development in a production environment to deliver unique AI-powered applications that address real problems.