Top Natural Language Processing (NLP) Jobs in Austin, TX

Design, build, and deploy LLM-powered agents and automations (using MCP) to integrate with Salesforce, HubSpot, Jira, and other tools. Create analytics dashboards and synthesize product telemetry into actionable insights for CSMs, consult with enterprise clients, and collaborate with Data Engineering to reduce churn and drive product adoption.

Own the end-to-end vision and roadmap for Boulevard's AI Receptionist. Define how AI handles voice and text client interactions, design handoffs to humans, set success metrics (autonomous resolution, CSAT, adoption, retention), drive business outcomes and pricing, gather deep customer insight from self-care businesses, and lead cross-functional teams to deliver trustworthy, high-quality AI conversational experiences.

Assist in designing high quality AI conversation models for customer contact centers. Collaborate with teams to build solutions that meet business objectives and maintain AI model quality.

Own end-to-end voice platform migration and scaling: LiveKit migration, real-time turn-taking, VAD, SIP/WebRTC, multi-agent handoff, training/fine-tuning voice models, inference cost optimization, and retrieval-based grounding using Supabase/pgvector.

Lead technical engagements with robotics customers to design and integrate voice AI into mobile robots, own POCs and technical evaluations, clear deployment roadblocks, collaborate with sales/product/services, and feed customer learnings into the product. Travel across Europe for onsite evaluations (20–30%).

Design, author, and iteratively optimize LLM evaluation prompts for Five9 AQM; define evaluation scope and pass/fail criteria with customers; select and analyze call samples; measure precision/recall; maintain a versioned prompt library; collaborate with QA and implementation teams; debug prompt failures; develop standards, templates, and support pre-sales demonstrations.

Entry-level AI communications intern working on routine, supervised tasks. Learns company policies, supports AI/LLM work, communicates technical concepts to non-technical stakeholders, and assists cross-functional projects. Prefers candidates pursuing CS/Data Science/related degrees with Python/JavaScript and LLM/API experience.

Build and own conversational voice AI products end-to-end: architect, implement, and deploy the platform. Design infrastructure, develop front-end and back-end systems, deliver reliable customer outcomes, and collaborate directly with the CTO to scale the product for enterprise customers.

Lead design of AI agent experiences—conversation and voice flows, multi-turn dialogs, escalation and error handling. Create user journeys, information architecture, wireframes, and clickable prototypes. Co-facilitate discovery workshops, ground decisions in user research, contribute to design systems, and ensure scalable, production-ready UX patterns for enterprise AI deployments.

Own strategy, roadmap, and execution for client-facing analytics and AI insights. Deliver dashboards, reports, and conversational NLQ analytics. Partner with data engineering, data science, and platform teams to shape semantic models and LLM-backed analytics. Drive adoption with Sales, Customer Success, and Implementation teams and use AI tools to accelerate product work.