Work with customers over the entire Archie product lifecycle: Lead discovery sessions, translate engineering challenges into AI use cases, design how Archie integrates into each workflow, and provide post-deployment support to ensure customer success.
Designing, implement, and refine customer integrations: connect Archie to engineering data sources and tools, iterate until it delivers measurable value.
Fine-tune and evaluate AI systems in production environments: identify, collect, and prepare customer data to fine-tune models. Source evaluation criteria and questions from customer sessions to validate improved engineering capability.
Work side by side with clients, PMs, and Architects to scope and deploy AI systems.
Build and integrate systems using LLMs, RAG pipelines, agent frameworks, vector databases and related tools.
Debug relentlessly and optimize for reliability in production, not just elegance in code.
Jobgether uses an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Their system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company.
Own deployment engineering projects, leading the technical execution of Parloa’s deployments inside large, complex enterprise environments.
Design for scale and resilience, architecting deployment solutions that meet enterprise-grade requirements for performance, reliability, and security.
Engineer solutions where none exist, building custom extensions, integrations, and configurations to close product gaps and meet enterprise requirements.
Parloa is a fast-growing startup in the world of Generative AI and customer service. Their voice-first GenAI platform automates customer service with natural-sounding conversations and has over 400+ employees in Berlin, Munich, and New York.
Design, build, and deploy AI Agents including custom tools, prompt engineering, orchestration workflows, and agent design patterns.
Contribute to the backend infrastructure powering Candidly's AI capabilities, including API development, data integrations, and data pipelines.
Work closely with stakeholders across product, design, engineering, and leadership to translate complex AI concepts into actionable strategies and features.
Candidly, founded in 2016, is the category leader with the market’s most comprehensive AI-driven student debt and savings optimization platform. They partner with hundreds of top employers, financial institutions, and retirement record keepers, positioning Candidly to serve more than 35 million Americans. Candidly is a high-growth, Series B startup, funded by leading investors with an international team of 70 (and counting).
ServiceNow is a global market leader that brings innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500. Their intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work.
Build AI-Powered Features: Design, develop, and deploy production-grade AI applications that solve real customer problems.
Architect Scalable Systems: Create robust backend architectures that support AI workloads, ensuring low latency and high reliability.
Drive AI Innovation: Implement and optimize agentic AI systems, RAG pipelines, and multi-agent workflows using modern LLM frameworks.
Procurify is the AI-enhanced procurement and AP automation platform for mid-market organizations. They help organizations take control of spend and save money as a remote-first company with a big heart and a strong ambition to modernize the way organizations manage business spend.
Drive the development and deployment of advanced AI models and systems that power Abacus products.
Oversee software development teams (30+ engineers) across multiple product lines, guiding architecture decisions and coding standards.
Lead critical projects in AI and data engineering, ensuring roadmap delivery and maintaining high quality standards.
Abacus Insights aims to unlock the power of data, enabling health plans to deliver the right care at the right time. Backed by $100M, they foster a bold, curious, and collaborative environment where innovation starts with people working together to make an impact.
Own complex, full-stack AI solutions end-to-end, from applied research to production deployment.
Set technical direction for ambiguous and high-impact use cases, while scaling the AI systems.
Mentor others, lead architectural decisions, and deepen Komodo’s AI-first culture.
Komodo Health is dedicated to reducing the global burden of disease by leveraging data. They have built the Healthcare Map, the industry’s largest view of the U.S. healthcare system. At Komodo, employees are ambitious, supportive, and passionate about delivering on its mission.
Build AI-Powered GTM Tools using data and AI capabilities to design internal tools, such as AI-assisted lead scoring and intelligent churn prediction.
Build High-Impact Customer Journey Experiences by developing self-serve interactive product demos and ROI calculators.
Own and Instrument Our GTM Data Stack by ensuring data is clean, connected, and actionable between product, website, and GTM systems like Salesforce and Hubspot.
Gather AI is pioneering a new era of warehouse intelligence with its vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, digitizing manual workflows. They're leading the charge in the rapidly evolving robotics industry, reshaping the global supply chain.
Define the long-term AI vision and technical direction for the product
Design and review architectures and system designs
Lead research and experimentation into new AI technologies
Solink provides businesses with tools to transform video security into real-time operational insights. They are a rapidly growing company with over 30,000 locations across 32+ countries and have been recognized by Deloitte’s Fast 50™ and Fast 500™ and as one of Ottawa’s Best Places to Work.
Work with other engineers on a wide variety of AI engineering tasks to improve our existing applied AI systems
Identify new opportunities to apply emerging AI capabilities to different parts of the Poe product
Take end-to-end ownership of applied AI systems - from prototyping, data pipelines, model optimization/evaluation to reliable deployment at scale
Quora's mission is to grow the world's collective intelligence. They have two platforms: Quora, a global knowledge sharing platform, and Poe, a platform to chat, explore and build with AI language models. They have a culture rooted in transparency, idea-sharing, and experimentation.
Own agent outcomes for strategic accounts end-to-end.
Deploy AI agents, drive automation rates, identify what's blocking progress, then build the platform fix
Work directly with enterprise CX leaders to design AI transformation roadmaps that you'll help execute
Siena is creating an operating system of AI agents that learn, remember, and act across every customer touchpoint. They are a small, distributed team that punches way above their weight; building leverage into everything they do.
Design and deliver scalable AI systems that connect models, data, and products.
Turn research prototypes into secure, reliable, production-ready services.
Build pipelines and serving layers that power adaptive, real-time features.
KnowBe4 is a cybersecurity company that puts security first, offering an AI-driven Human Risk Management platform. They empower over 70,000 organizations worldwide to strengthen their security culture and transform their workforce into their strongest security asset.
Design, build, and operate customer-facing features integrated into core product workflows.
Build and maintain internal services that provide stable, reusable interfaces for other engineers.
Bring AI workflows to production with observability, fallback strategies, and consideration for cost.
Turquoise Health aims to simplify healthcare pricing, increase transparency, and lower costs. They are a Series B startup backed by top VCs with a passion for improving healthcare and a team of ambitious and well-rounded individuals.
Design, build, and optimize high-performance systems in Python supporting AI data pipelines and evaluation workflows
Develop full-stack tooling and backend services for large-scale data annotation , validation, and quality control
Improve reliability, performance, and safety across existing Python codebases
Alignerr connects top technical experts with leading AI labs to build, evaluate, and improve next-generation models. We work on real production systems and high-impact research workflows across data, tooling, and infrastructure.
Design, build, and optimize high-performance systems in Python supporting AI data pipelines and evaluation workflows
Develop full-stack tooling and backend services for large-scale data annotation , validation, and quality control
Improve reliability, performance, and safety across existing Python codebases
Alignerr connects top technical experts with leading AI labs to build, evaluate, and improve next-generation models. They work on real production systems and high-impact research workflows across data, tooling, and infrastructure.
Design, build, and optimize high-performance systems in Python supporting AI data pipelines and evaluation workflows.
Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control.
Improve reliability, performance, and safety across existing Python codebases.
Alignerr connects top technical experts with leading AI labs to build, evaluate, and improve next-generation models. They work on real production systems and high-impact research workflows across data, tooling, and infrastructure.
Implement production AI / ML workloads using Ray and Anyscale.
Advise customers on ML system architecture.
Partner with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows.
Anyscale is on a mission to democratize distributed computing and make it accessible to software developers. They are commercializing Ray, an open-source project creating an ecosystem of libraries for scalable machine learning and are backed by Andreessen Horowitz, NEA, and Addition.
Provide technical leadership on a new team prototyping and experimenting with new AI features
Productionize and ship AI integrations into Modern Health’s core product
Collaborate with cross-functional teams to deliver product features on time
Modern Health is a mental health benefits platform for employers, offering access to various resources for emotional, professional, social, financial, and physical well-being. They are the fastest entirely female-founded company in the U.S. to reach Unicorn status, with a "It Takes a Village" culture centered around high empathy and accountability.
Design, build, and optimize high-performance systems in Python supporting AI data pipelines and evaluation workflows
Develop full-stack tooling and backend services for large-scale data annotation , validation, and quality control
Improve reliability, performance, and safety across existing Python codebases
Alignerr connects top technical experts with leading AI labs to build, evaluate, and improve next-generation models. They work on real production systems and high-impact research workflows across data, tooling, and infrastructure.
Lead domain-specific model optimization using PEFT (LoRA/QLoRA) and knowledge distillation to balance cost, latency, and reasoning capability.
Build next-gen Retrieval-Augmented Generation pipelines using hybrid search, cross-encoders, and self-correcting retrieval loops.
Design and deploy multi-agent systems using frameworks like LangGraph or CrewAI, enabling autonomous task planning and tool-use (Function Calling).
ServiceNow is a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Their intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work.