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Propio LS LLC

Senior AI Engineer

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What they do

A Generative Artificial Intelligence Engineer develops, designs, and manages generative models and algorithms that support the generation of new content in the form of images, text, audio, and other multimedia. They utilize GPTs, GANs, VAEs, and other deep learning architectures to craft systems capable of generating data. May work with data scientists, machine learning engineers, and software developers.

$110,502 / year median in Kansas

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Job Description

Senior AI Engineer Propio

LS LLC - 5.0

Overland Park, KS Job Details Full-time 12 hours ago Qualifications AI models Software engineering HIPAA compliance Full-stack development Infrastructure as Code (IaC) Enterprise software

HIPAA AI

platforms (beyond public GPTs) Computational framework Enterprise software systems development Production systems AWS Machine intelligence Continuous integration Developing large-scale AI models Cloud automation DevOps automation Machine learning frameworks Python Full Job Description Overland Park, KS (Hybrid)

• Engineering Job Type Full-time Description Propio Language Services is a top-five global language services provider and the fastest-growing company in the industry. Operating at nine-figure scale across healthcare, legal, and other sectors, Propio delivers high-quality, real-time multilingual interpretation, translation, and localization services. Driven by cutting-edge technology and exceptional service, we create seamless experiences that bridge communication gaps across languages, cultures, and communication channels. We are looking for a highly skilled and hands-on Senior AI Engineer to lead the design, development, and productionization of advanced AI systems. This role is for someone who can operate as both a technical leader and a strong individual contributor. You will own complex AI initiatives end-to-end—from problem definition, research, experimentation, and architecture through implementation, evaluation, deployment, and production optimization. This is not a people-management-only or project-coordination role. You are expected to remain deeply hands-on, write production code, review critical implementations, investigate difficult technical problems, and lead by building.

Key Responsibilities:

Own the architecture, development, and delivery of enterprise-grade AI systems from concept to production, including LLM, generative AI, agentic, multimodal, speech AI, and machine learning systems. Prototype, build, and deploy real-time AI applications and infrastructure for speech, voice agents, LLM-powered workflows, and other latency-sensitive AI experiences. Lead the development of AI capabilities including agent orchestration, tool calling, RAG, structured generation, memory, reasoning workflows, guardrails, and evaluation systems. Evaluate and select models, architectures, frameworks, and technologies based on measurable tradeoffs across quality, latency, reliability, scalability, and cost. Stay current with emerging AI research and industry trends, Rapidly prototype new AI approaches and convert successful experiments into reliable, scalable, and maintainable production systems. Demonstrated ability to mentor engineers, conduct high-quality design and code reviews, and influence technical direction across a team.

Requirements Qualifications:

Master's degree in Engineering, preferably in Computer Science, Statistics, Data Science, or a related field, or equivalent relevant work experience. 7+ years of hands-on full-stack software engineering experience, with significant experience building production-grade AI/ML backend systems and strong proficiency in Python. 3+ years of experience building production-grade modern AI systems, particularly real-time speech AI, speech-to-text, text-to-speech, voice agents, conversational AI, multimodal systems, or agentic systems. Experience building and operating production systems on cloud platforms in AWS, including production-grade CI/CD and infrastructure-as-code tools such as AWS CDK. Experience with real-time speech AI systems, real-time audio processing, or other latency-sensitive applications, using technologies or platforms such as OpenAI, Deepgram, Whisper, Hugging Face Transformers, or similar tools. Experience building multi-agent or complex agent orchestration systems using LangChain or similar frameworks. Experience working in healthcare, legal, or other regulated environments, including familiarity with AI safety, HIPAA, PHI, and Section 1557 requirements. Prior experience with multilingual AI systems or low-resource language challenges is a plus. This may not be the right role for you if: You prefer primarily coordinating projects rather than designing and building systems yourself. Your AI experience is primarily limited to integrating third-party AI APIs without owning the underlying architecture, evaluation, reliability, or production behavior. You rely primarily on prompt experimentation without systematic evaluation, metrics, testing, or engineering rigor. You have primarily built demos or prototypes and have limited experience operating AI systems in production. You prefer working from detailed specifications rather than owning ambiguous technical problems from problem definition through implementation. You are looking for a people-management-only role. You are uncomfortable diving into code, debugging production issues, or reviewing critical technical implementations. You are uncomfortable making technical decisions when information is incomplete and there is no obvious solution. #LI-JS1 #LI-Hybrid Notice of AI Use in Job Application Review As part of our commitment in creating a fair, efficient, and consistent hiring process we may use artificial intelligence (AI) to help our recruiting teams organize, summarize, and analyze information provided by candidates, including resumes, application responses, and other materials submitted during the application process.



AI may be used to identify patterns, highlight relevant skills, and experience, and assist in comparing a candidate's qualifications with the requirement of a specific role. These tools are to improve efficiency and consistency while supporting more informed hiring decisions, which will ultimately be made by the hiring team.