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

Role Description We are hiring a senior, hands-on engineer to partner directly with the Head of Products in architecting and building a new multi-agent orchestration and communication platform from the ground up. In the early phase, this person will act as a high-trust technical counterpart focused on architecture, core implementation, and platform design. As the product matures, they will become the application owner and help lead a growing offshore team supporting ongoing development. What you'll own - A production-grade orchestration layer for coordinating multiple specialized agents, tools, and workflows. - A modern agent-facing UI built around the Vercel AI / Agent SDK ecosystem. - Persistent and contextual memory using a memory SDK. - Support for multimodal inputs, including text, files, and other rich inputs. - A Microsoft Teams integration for agent-driven communication and workflow execution. - A set of purpose-built agents, beginning with a Statement of Work generation agent and a Dynamics 365 intelligence / integration agent. - Architectural decisions around where capabilities should live: as orchestrated tools, as specialist agents, or as standalone platform services. Core responsibilities - Partner directly with the Head of Products to define the platform architecture, implementation strategy, and long-term technical direction. - Architect and build a reliable multi-agent orchestration framework for coordinating specialized agents, tool calls, memory systems, and enterprise integrations. - Design clear communication patterns between orchestrator, agents, tools, memory providers, and external systems. - Build the initial platform capabilities, including agent UI, memory integration, multimodal workflows, and enterprise communication channels. - Create a Statement of Work generation capability that can produce structured Word documents from templates, business rules, and configurable user inputs. - Design a templating and administration model that allows non-technical users to customize output structure and business logic without engineering support. - Design a Dynamics 365 agent or integration layer capable of extracting, interpreting, and operationalizing complex CRM context more effectively than conventional copilots. - Establish strong patterns around observability, tracing, evaluation, retries, fallbacks, safety, and reliability for AI-native systems. - Serve as the long-term application owner as the platform grows, ensuring architectural consistency, engineering quality, and delivery discipline. - Provide technical leadership for future supporting engineers, including an offshore development team, through architecture guidance, code reviews, work decomposition, and mentoring. Qualifications - 7+ years of software engineering experience building production systems. - Deep experience delivering LLM-based systems or AI-enabled products in production, not just prototypes or demos. - Strong understanding of agent orchestration, including multi-agent coordination, routing, tool use, memory, workflow state, and human-in-the-loop patterns. - Experience with one or more agent ecosystems such as Vercel AI SDK, LangChain, LangGraph, OpenAI Agents SDK, or similar frameworks. - Strong understanding of MCP-style integration patterns, tool contracts, and external-system interoperability. - Experience with vector databases, embeddings, retrieval pipelines, and semantic memory strategies. - Strong experience designing and operating cloud-native services on Azure. - Solid software engineering fundamentals across architecture, debugging, reliability, and scaling. - Experience working in GitHub Enterprise environments. - Prior experience acting as a technical lead, system owner, staff engineer, or principal engineer on a meaningful product or platform. Preferred qualifications - Experience with graph-based orchestration and graph databases. - Experience with Convex or other real-time application backends. - Experience with mem0.ai, cortexmemory.dev, or similar memory-layer tooling. - Experience integrating AI systems into Microsoft Teams. - Experience with Dynamics 365 / CRM data models, APIs, and workflow patterns. - Experience generating structured business artifacts such as proposals, statements of work, reports, or Word documents. - Experience building configurable template systems for non-technical business users. - Experience with multimodal pipelines involving text, documents, images, and file understanding. - Experience leading distributed and/or offshore teams. Company Description Cyclotron is an Equal Opportunity Employer. Cyclotron values diversity, equity and inclusion, and aims to practice DE&I in all that we do.

• Architect and build AI-powered systems that power our entire GTM motion • Own the technology stack, partner with stakeholders to define workflows • Deploy AI agents and apps • Continuously improve how the company acquires, activates, and grows customers • 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 • 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 • Design and deploy AI-driven workflows and agents that augment GTM teams. • Support a hybrid GTM model where open-source and self-serve users graduate into paid, sales-assisted customers • Partner closely with Product & Marketing to turn usage insights into GTM leverage • Build the infrastructure that allows the GTM team to learn quickly and iterate with confidence • Create tight feedback loops between users, product signals, and GTM actions • Continuously optimize workflows, models, and automation based on real outcomes.

• Designing, developing, and operationalizing state-of-the-art AI solutions, including large language models (LLMs) • Building and integrating scalable AI/ML systems • Collaborating on software development efforts • Driving innovation to advance Mercy’s vision of personalized, predictive, and proactive care