Define and evolve enterprise AI platform architecture, act as a senior technical advisor for AI adoption, evaluate and integrate AI capabilities across ecosystems, and continuously research emerging AI technologies to enhance platform capabilities.

Design and develop intelligent applications using advanced LLMs and generative AI technologies. Integrate diverse data sources and optimize retrieval performance while delivering high-quality prototypes for next-generation advisor assistance tools.

Title: Prompt Engineer Location: Austin United States Job Description: Description Why Join Sensi.AI Sensi.AI is transforming the world of home care through agentic AI - and we're just getting started. As a hyper-growth startup, every team member has the opportunity to make a real impact on people's lives while working as part of a global, collaborative team in a flexible hybrid environment. About the Role We are looking for a Prompt Engineer to design, optimize, and continuously improve multi-turn conversational experiences across multiple Sensi.AI product lines. This role combines linguistic creativity, AI prompt engineering, and real-world experimentation. You'll work closely with product managers, who will provide requirements and prioritization, while you focus on crafting and iterating prompts, testing in real-world scenarios, and delivering natural, trustworthy interactions. This role is based in Austin, TX, with a hybrid work setup, combining in-office collaboration with remote flexibility. Key Responsibilities Conversational Design and Prompting - Design multi turn dialogue flows for text and voice agents with context awareness and memory handling. Define personalities and tone across products and agents. - Create multilingual prompt strategies and develop reusable templates and frameworks to speed development. Continuous Testing and Improvement - Test prompts with recordings, transcripts, and simulations before and after launch. Analyze live interactions to spot hallucinations, tone issues, dead ends, and token inefficiency. - Iterate quickly to improve quality, safety, and naturalness and use analytics and qualitative insights to measure success. Collaboration and Delivery - Partner with product managers on requirements and goals and work with engineers to integrate prompts within technical constraints. - Coordinate updates across multiple agents with version control for a unified experience and support compliance and privacy standards. Documentation and Knowledge Sharing - Maintain a prompt library with flows, system prompts, and version history and set guidelines for tone, multilingual consistency, and testing. - Share insights and learnings with the broader product and AI teams. Requirements - Proven experience designing multi-turn conversational systems, such as chatbots, voice assistants, or customer service agents. - Strong skills in prompt engineering techniques (e.g., few-shot, chain-of-thought, RAG pipelines). - Ability to define consistent, persona-driven conversational styles across multiple agents and products. - Familiarity with LLM APIs (OpenAI, Anthropic, etc.) and conversational frameworks (e.g., LangChain). - Excellent writing and linguistic skills, with attention to tone, clarity, and cultural sensitivity. - Basic programming skills (Python preferred) for testing and prototyping prompts. Nice-to-Have - Background in healthcare, caregiving, or other regulated industries. - Multi-lingual proficiency. Sensi celebrates diversity and uphold equal opportunity in our hiring practices. Our approach fosters an inclusive environment that sparks innovation and reflects the vibrant communities we serve. All persons shall have the opportunity to be considered for employment without regard to any characteristic protected by applicable federal, state, or local laws and ordinances.

The future of AI — whether in training or evaluation, classical ML or agentic workflows — starts with high-quality data. At HumanSignal, we’re building the platform that powers the creation, curation, and evaluation of that data. From fine-tuning foundation models to validating agent behaviors in production, our tools are used by leading AI teams to ensure models are grounded in real-world signal, not noise. Our open-source product, Label Studio, has become the de facto standard for labeling and evaluating data across modalities — from text and images to time series and agents-in-environments. With over 250,000 users and hundreds of millions of labeled samples, it’s the most widely adopted OSS solution for teams working on building AI systems. Label Studio Enterprise builds on that traction with the security, collaboration, and scalability features needed to support mission-critical AI pipelines — powering everything from model training datasets to eval test sets to continuous feedback loops.We started before foundation models were mainstream, and we’re doubling down now that AI is eating the world. If you're excited to help leading AI teams build smarter, more accurate systems — we’d love to talk. About the Role We’re looking for an ambitious AI Engineer to transform how our go-to-market team operates. San Francisco, Austin, or Lisbon are preferred locations where you can collaborate with team members, but the position is remote or hybrid. As the founding GTM engineer, you will architect and build the AI-powered systems that power our entire GTM motion, owning the technology stack, partnering with stakeholders to define the workflows, deploying AI agents and apps, and continuously improving how the company acquires, activates, and grows customers. This is a highly hands-on role for someone who enjoys shipping systems, experimenting rapidly, and solving messy real-world problems with software. Why This Role Matters This role is a force multiplier for the entire company. You’ll build the infrastructure that allows the GTM team to move faster, learn faster, and scale without proportional headcount. You’ll help us: - Turn GTM from a set of tools into a cohesive, intelligent system - Scale workflows without scaling headcount - Improve signal quality and timing for marketing and sales - Increase learning velocity across the entire funnel - Shape how an open-source, bottom-up product grows into enterprise adoption What You’ll Do Build & Automate the foundational GTM AI stack - Design, build, and maintain AI systems across marketing, PLG, sales, and post-signup activation - Own integrations and workflows across tools like CRM, marketing automation, product analytics, data warehouse, enrichment tools, and internal services - Build internal tools and lightweight services that accelerate GTM teams - Replace manual workflows with scalable, automated systems AI-Powered Systems & Agents Design and deploy AI-driven workflows and agents that augment GTM teams. Examples include: - Lead qualification, inbound lead routing, and enrichment - Personalized lifecycle marketing and outbound messaging - Sales assist tools for deal intelligence and account research - Automated account insights, pipeline analysis, and deal lifecycle management - User onboarding, activation, and expansion signals You’ll continuously improve these systems using real performance data and feedback loops. Growth: PLG + Sales-Assisted Motion - Support a hybrid GTM model where open-source and self-serve users graduate into paid, sales-assisted customers - Partner with Data & Growth to build systems that surface product signals (usage, intent, readiness) to marketing and sales teams at the right time - Partner closely with Product & Marketing to turn usage insights into GTM leverage Experimentation & Learning Build the infrastructure that allows the GTM team to learn quickly and iterate with confidence. - Design and run experiments across acquisition, activation, conversion, and expansion - Build experimentation frameworks (feature flags, A/B testing, measurement systems) - Instrument systems to capture reliable data and insights - Rapidly iterate based on results, not assumptions Feedback Loops & Continuous Improvement Create tight feedback loops between users, product signals, and GTM actions. - Partner with head of , accessible, and actionable across teams - Turn qualitative and quantitative insights into system improvements - Continuously optimize workflows, models, and automation based on real outcomes What We’re Looking For Core Skills This is fundamentally an engineering role, not traditional GTM operations. We’re looking for someone who enjoys building systems, not managing tools. - Strong engineering background (software, data, or growth engineering) - Comfortable shipping production code (APIs, services, scripts, internal tools) - Experience working with data pipelines, analytics, and experimentation frameworks - Hands-on experience with AI/LLMs, prompt engineering, or agent-based systems Collaboration & Ownership - Ability to work cross-functionally with Product, Engineering, Marketing and Sales - Comfortable operating with ambiguity and defining the problem as you go - Strong communicator who can translate between technical and GTM stakeholders Nice to Have - Experience with open-source or developer-focused products - Familiarity with CRM systems (e.g., Salesforce, HubSpot), CDPs, and marketing automation - Experience building internal tools for sales or marketing teams - Prior work in B2B SaaS, data, or AI-first companies