About the Role:
We’re looking for a Backend Engineer to contribute to a next-generation security initiative. You’ll be part of a small, highly technical team working on novel approaches to secure systems - with a focus on cryptography, automation, and AI-powered analysis. You’ll work closely with senior engineers and contribute hands-on to the codebase across the stack. This role involves hands-on development, learning opportunities, and collaboration across engineering, product, and design.

Day to Day:

• Contribute to the design, development, and delivery of features across the product
• Write clean, maintainable code for back-end systems deployed in AWS or GCP
• Collaborate with AI and cryptography specialists
• Work with the product manager to understand requirements and help the team plan architecture, data flows, API specs, and testing strategies
• Follow established engineering practices and participate in team discussions around process and quality
• Participate in customer-driven development and iterate based on feedback
• Write automated tests for load, performance, and error handling

What you bring to the table:

• 3+ years of hands-on software engineering experience for backend development
• Excellent TypeScript and Node.js coding experience
• AWS experience in containers (EKS, ECS) and serverless systems
• Relational, key/value, and graph datastore experience with schema management
• API design, data modeling, secure service development, database systems
• Has a focus on quality code, error handling, and high availability
• A thoughtful, pragmatic approach to solving technical problems in a fast-paced environment
• At least upper-intermediate level of spoken and written English

Extra Credit:

• Versed in Python coding and environments
• Experience with GCP systems
• Experience with applied cryptography, especially key management, TLS, or post-quantum algorithms
• Familiarity with agent-based architectures or systems that scan and orchestrate actions across distributed environments
• Knowledge of AI/ML systems, particularly LLM integration or agent-style reasoning patterns
• Experience managing LLM agents to increase both speed and quality of code generation and tests
• Exposure to security tools, vulnerability detection platforms, or compliance automation
• Prior experience working on developer-facing or infrastructure-heavy products

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience. 

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries. 

We are proud of: 

• The work we do and the innovation we drive 
• Our values of share, care and dare 
• A workplace culture that fosters creativity, diversity and autonomy 
• Our borderless, global framework, which enables seamless collaboration 

The role  

We are looking for a Senior Python + AI Engineer, to join the existing backend team.

You will thrive in this role if you are: 

• A curious problem solver who challenges the status quo 
• A collaborator who values teamwork and knowledge-sharing 
• Excited by the intersection of technology, creativity and data 
• Experienced in Agile methodologies and consulting (a plus) 

Must have qualifications

To be considered for this role, you must meet the following essential qualifications: 

• Strong experience with Python (3.10+) and async programming in production
• Hands-on FastAPI delivery (REST APIs, OpenAPI), experience with Pydantic, SQLAlchemy and Alembic migrations
• Experience with Redis would be a plus for caching and pub/sub where needed is a plus
• Working experience with TypeScript and React (Next.js) is a plus

• Practical experience building LLM-powered applications with tool-calling and agentic patterns
• Strong familiarity with LangChain and LangGraph for stateful, multi-agent orchestration
• Experience developing or integrating MCP servers/clients
• Experience working with AI code generation tools (e.g., Cursor, GitHub Copilot etc.)
• Practical experience with RAG. Would be a plus Knowledge Graphs and Graph RAG

• Familiarity with Docker in production environments
• Familiarity with Azure delivery patterns and CI/CD workflows
• Working knowledge of LLM observability (e.g., Langfuse, LangSmith), structured logging, and trace-based debugging

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn. 

Commitment to reaching all kinds of people 

We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all. 

The benefits  

This is a Full time position based in Ukraine. 

Beyond a competitive compensation package, we offer: 

• Mental and physical health:
  • Medical insurance 
  • Sports reimbursement budget 
  • Home office support 
  • A number of free psychological and legal consultations 
  • Maternity and paternity leave support 
    
    
• Personal and professional development:
  • Internal workshops and learning initiatives 
  • English language classes compensation 
  • Professional certifications reimbursement 
  • Participation in professional local and global communities 
  • Growth Framework to manage expectations and define the steps to move towards the selected career 
  • Mentoring program with the ability to become a mentor or a mentee to grow to a higher position 
  • Valtech Ukraine has a system of progressive benefits packages in place — the longer you stay with the company — the more benefits you get. 

Your application process

Once you apply, our Talent Acquisition team will review your application. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential.

⚠️ Beware of recruitment fraud!

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know. 

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world. 

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more. 

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate. 

Are you ready to create what’s next? Join us.

WE ARE AMDARIS

We fuse together exceptional talent who deliver outstanding software solutions. Our approach has helped us grow 60% in 2021, 94% in 2022 and our future is even bigger. With exciting growth plans and cutting-edge projects, there has never been a better time to join our incredible team.

Role Overview

We are looking for a Principal Engineer to own the architecture, development, and evolution of our content development and distribution pipelines across a multi-platform LMS landscape. You will drive the adoption of AI-assisted content generation workflows, design agentic systems that reduce manual effort at scale, and serve as a hands-on technical lead for a small, high-impact engineering team.

Key Responsibilities

–Design, build, and maintain robust content development and distribution pipelines that serve a diverse LMS ecosystem (e.g.H5P, SCORM/xAPI standards).
–Design and implement agentic AI workflows for automated and semi-automated content generation, curation, tagging, and quality assurance.
–Rapidly prototype new capabilities using AI-native tooling (LLM APIs, vector stores, embedding pipelines) to validate ideas before full-scale engineering investment.
–Lead and mentor a team of 4–6 engineers through technical design, code review, and day-to-day engineering delivery.
–Define and enforce standards for content schema, metadata, versioning, and pipeline observability.
–Partner with product, instructional design, and data teams to translate learning content requirements into scalable technical solutions.
–Evaluate and integrate third-party content and AI services, ensuring compliance with data governance and privacy standards.
–Drive continuous improvement for pipeline reliability, latency, and throughput.

Position Requirements

–8+ years of software engineering experience, with at least 3 years in a senior or principal-level role owning complex data or content pipelines.
–Deep experience with LMS platforms and content standards (H5P, SCORM, xAPI/Tin Can, LTI).
–Proven track record designing and operating agentic or multi-step AI workflows using LLMs (e.g. OpenAI, Anthropic, Gemini), orchestration frameworks (e.g. LangChain, LlamaIndex, CrewAI), and tool use / function calling patterns.
–Strong prototyping instincts — comfortable building working proof-of-concepts quickly with AI coding assistants and modern tooling, then handing off or scaling the result.
–Experience leading small engineering teams: setting technical direction, running design reviews, and growing engineers through coaching and feedback.
–Proficiency in at least one backend language (Python, Node.js, or Java/Kotlin) and familiarity with cloud-native infrastructure (AWS, GCP, or Azure).
–Solid understanding of content storage, CDN distribution, and asset management at scale.
–Clear communicator who can translate technical trade-offs for non-technical stakeholders.

Nice to have

–Experience in EdTech or corporate learning environments at scale.
–Familiarity with RAG (Retrieval-Augmented Generation) architectures for content search and personalization.
–Exposure to fine-tuning or evaluation frameworks for AI-generated educational content.
–Understanding of accessibility standards for digital learning content (WCAG, Section 508).

Core Technologies

Python / Node.js · LLM APIs · LangChain / LlamaIndex · H5P / SCORM / xAPI · LTI · Vector stores · Cloud (AWS / GCP / Azure) · CDN & asset pipelines · REST / GraphQL · CI/CD

About Sisense

Sisense is a leading AI-powered Analytics Platform as a Service (AnPaaS) that empowers product teams and developers to embed conversational, predictive, and agentic intelligence directly into applications and workflows. Our API-first, developer-first platform turns complex data into faster, smarter, actionable decisions for over 2,000 global customers across financial services, retail, healthcare, and technology.

With the recent launch of Sisense Intelligence (Intelligence Assistant, MCP server, Managed LLM), we are accelerating innovation in embedded analytics at scale.

The Role

As a DevOps Engineer, you will play a key role in designing, building, and maintaining the scalable, reliable infrastructure that powers Sisense’s AI-powered embedded analytics platform. You will work on cloud-native environments, CI/CD pipelines, automation, monitoring, and production stability — helping ensure our platform delivers high performance and developer experience at scale.

This is a hands-on role with significant ownership and impact on both internal development velocity and customer-facing reliability.

Key Responsibilities

• Design, implement, and maintain scalable infrastructure for our SaaS platform using modern cloud-native technologies.
• Build and improve CI/CD pipelines, automation tools, and deployment processes to increase development velocity and reliability.
• Own production environments: monitoring, troubleshooting, performance tuning, and incident response.
• Work closely with development teams to support infrastructure needs for new features and services.
• Research, evaluate, and introduce new tools and technologies to improve platform efficiency and observability.
• Develop and maintain Infrastructure as Code (Terraform, Crossplane, Helm, Argocd, etc.).
• Collaborate on improving observability, logging, and alerting across distributed systems.
• Participate in a rotating on-call schedule to provide 24/7 coverage for incident response and production support.

Requirements

• 4–6+ years of hands-on DevOps or SRE experience.
• Strong proficiency with Kubernetes and cloud platforms (AWS, Azure, or GCP) AWS preferred.
• Solid experience with Infrastructure as Code tools (Terraform /crossplane / Terragrunt, Helm, argocd).
• Excellent Linux systems knowledge and scripting skills (Bash, Python, or Go preferred).
• Experience building and maintaining CI/CD pipelines and automation frameworks (gitlab-ci ,github-actions and jenkins).
• Deep familiarity with monitoring tools (fluentd , fluent-bit, promethus and grafana stack , opentelemetry )
• Strong problem-solving and troubleshooting skills in high-scale production environments.
• Good communication skills and ability to work effectively in a remote, distributed team.
• Advanced English.

Nice to Have

• Experience with Node.js / TypeScript environments.
• Familiarity with multiple linux distros (ubuntu-debian , redhat , oracle)
• Background in data-intensive or analytics platforms.
• Familiarity with OpenTelemetry, monitoring tools, or distributed tracing.
• Experience supporting customer-facing SaaS platforms at scale.

Why Join Sisense

This is a high-impact role where you’ll work on the infrastructure behind cutting-edge embedded AI analytics. You’ll join a talented global engineering team, enjoy competitive compensation, meaningful equity, and the opportunity to solve complex technical challenges in a fast-growing company.

If you’re a strong DevOps Engineer who loves building reliable, scalable systems and wants to work on AI-powered data solutions, we’d love to hear from you.

Sisense is the leading AI-powered analytics platform that helps software companies and product teams build smarter, embedded analytics experiences directly into their applications. With Sisense Intelligence - our suite of agentic AI capabilities - we empower application builders to deliver governed conversational analytics, accelerate development with natural language tools, and turn data into actionable insights and revenue.

We're investing heavily in the foundational platform that powers this vision and are looking for a sharp, technical Product Manager to help shape the next generation of our Data & Analytics Platform. You'll drive the core infrastructure, APIs, developer tools, and AI-enablement capabilities that make Sisense the most flexible and powerful choice for embedding intelligence at scale.

We are looking for…

The Sisense Product Team is seeking a highly motivated Technical Product Manager with a deep passion for platform products, data systems, developer experience, and AI-powered analytics.

This role suits someone who thrives working hand-in-hand with engineering teams, dives deep into technical architecture, and excels at turning complex platform challenges into clear, customer-focused product direction. You will own critical platform foundations that enable application builders to create scalable, secure, composable, and intelligent analytics experiences - from low-code/no-code tools to pro-code extensibility.

We're looking for a curious, analytical, and hands-on PM who is excited by deeply technical areas: infrastructure, platform services, data modeling, APIs, developer SDKs, AI integration, and the capabilities that power modern embedded analytics.

Requirements

• 1–3 years of experience in Product Management, Technical Product Management, Solutions Engineering, Software Engineering, or a similar role, with a strong technical foundation.
• Experience with platform products, developer tools, APIs, data platforms, infrastructure, embedded analytics, or AI/ML technologies is a strong advantage.
• Solid technical understanding and comfort engaging in discussions on architecture, system design, scalability, reliability, APIs, data modeling, and technical trade-offs.
• Ability to break down complex technical concepts into clear product requirements, user stories, prioritization frameworks, and actionable roadmaps.
• Excellent English communication skills; ability to collaborate effectively with technical (engineering, architecture) and non-technical (go-to-market, customers) stakeholders.
• Customer-obsessed mindset, with a talent for deeply understanding the needs of application builders, developers, and end-users, then translating them into high-impact platform solutions.
• Hands-on and detail-oriented, with a natural tendency to ask “why,” challenge assumptions, and relentlessly validate that delivered capabilities solve real problems.
• Comfortable working side-by-side with engineers on feature design, technical dependencies, implementation trade-offs, and connecting platform work to measurable customer and business value.
• Proven ability to lead product capabilities end-to-end: from discovery and validation through delivery, launch, and adoption.
• Strong prioritization and execution skills in a complex, cross-functional environment; bias for action and ownership.
• Experience working with AI technologies, LLMs, agentic systems, or shipping AI-powered capabilities is a significant advantage.

Your Responsibilities

• Own and drive key components of the Sisense Platform, focusing on foundational technical capabilities, infrastructure, APIs, data services, and developer-facing tools that power Sisense Intelligence and embedded experiences.
• Define clear product requirements for platform services, Compose SDK, MCP connectivity, AI integration layers, internal infrastructure, and extensibility features; drive them from discovery to launch and post-launch optimization.
• Partner closely with Engineering, Architecture, and Design teams to make smart, balanced product and technical decisions that balance speed, scalability, reliability, and innovation.
• Collaborate with customers, product leaders, and go-to-market teams to uncover needs, validate problems, and prioritize platform investments that deliver maximum impact for application builders.
• Work with other PMs to ensure seamless end-to-end experiences that let developers and product teams leverage the full power of Sisense’s AI-driven analytics engine.
• Prioritize backlog based on customer value, technical strategy, scalability, security, developer experience, and long-term platform health.
• Communicate roadmap, strategy, and decisions transparently to stakeholders across Product, Engineering, Support, Sales, Marketing, and Customer Success.
• Create high-quality internal and external documentation, presentations, and enablement materials that clearly articulate the value and usage of platform capabilities.
• Contribute to and help evolve Sisense’s overall platform strategy, ensuring it remains scalable, extensible, secure, AI-native, and developer-friendly.

Why you should join our team

Sisense is redefining embedded analytics by moving far beyond traditional dashboards. We deliver a full-stack Analytics Platform as a Service (AnPaaS) that combines powerful data modeling, composable embedding tools, and Sisense Intelligence - our agentic AI suite (including Assistant, Managed LLM, and MCP server) - to help application builders prototype faster, embed conversational analytics, and deliver governed, actionable insights directly inside their products.

In this role, you'll tackle challenging technical problems at the heart of the platform, influence foundational decisions that impact thousands of developers and end-users, and work alongside talented teams across Product, Engineering, Design, and Go-to-Market. If you’re passionate about platform thinking, technical depth, AI enablement, and building the infrastructure that powers other great products, this is your chance to make a significant impact in a fast-evolving space.

About Sisense

Sisense is a leading AI-powered Analytics Platform as a Service (AnPaaS) that empowers product teams and developers to embed conversational, predictive, and agentic intelligence directly into applications and workflows. Our API-first, developer-first platform turns complex data into faster, smarter, actionable decisions for over 2,000 global customers across financial services, retail, healthcare, and technology.

With the recent launch of Sisense Intelligence (Intelligence Assistant, MCP server, Managed LLM), we are accelerating the next wave of embedded analytics innovation.

The Role

As a Full-Stack Engineer (Node/React), you will play a key role in building and enhancing the core platform that powers embedded AI analytics. You will work across the full stack — from backend services and APIs to modern frontend interfaces — helping to deliver high-performance, scalable, and delightful experiences for both developers and end users.

This is a hands-on role with real ownership, where you’ll contribute to features that directly impact how customers embed intelligence into their products.

Key Responsibilities

• Develop and maintain full-stack features using Node.js (backend) and React (frontend).
• Build and optimize scalable APIs and backend services that power our embedded analytics capabilities.
• Create responsive, performant, and user-friendly frontend interfaces.
• Collaborate closely with Product, Design, and other Engineering teams to deliver high-quality solutions.
• Participate in code reviews, architectural discussions, and technical decision-making.
• Contribute to improving platform performance, reliability, and developer experience.
• Help implement features related to Sisense Intelligence (agentic AI, conversational interfaces, predictive analytics).

About You

• 3-5 or more years of full-stack development experience with strong proficiency in Node.js and React.
• Solid understanding of modern web technologies, REST/GraphQL APIs, and frontend architecture.
• Strong problem-solving skills and ability to break down complex requirements into clean, maintainable code.
• Comfortable working independently in a remote-first environment with high ownership.
• Advanced English (team in Israel)
• Passion for best coding practices, user experience, and using AI tool to enhance development responsibly.

Nice to Have

• Experience with TypeScript, Next.js, or modern frontend frameworks.
• Experience building scalable backend services and responsive user interfaces.
• Exposure to cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
• Background in data-intensive applications, BI/analytics tools, or developer platforms.
• Familiarity with AI/ML concepts or building AI-powered user experiences.

OUR BENEFITS:

• We’re all working remotely.
• We hire only people we trust. All Sisensers join the company without a probation period.
• We believe all Sisensers should be owners of our company’s success. We grant all employees stock options that start vesting on Day One.
• We support a work-life balance philosophy and provide unlimited vacations (flexible time off) and additional long weekends to all Sisensers.
• We support professional growth with access to the modern learning platform.
• We care about each other. All team members have extended medical insurance.
• We provide Sisensers with a sports reimbursement to support physical fitness and mental well-being.

Sisense is a leading AI-powered Analytics Platform as a Service (AnPaaS) that empowers product teams and developers to embed conversational, predictive, and agentic intelligence directly into applications and workflows. Our API-first, developer-first platform turns complex data into faster, smarter, actionable decisions for over 2,000 global customers across financial services, retail, healthcare, and technology.

With the recent launch of Sisense Intelligence (Intelligence Assistant, MCP server, Managed LLM), we are accelerating the next wave of embedded analytics innovation.

The Role

As a Senior Full-Stack Engineer (Node/React), you will be a driving force behind the evolution of our core platform, powering the next generation of embedded AI analytics. This is a high-impact, hands-on role where you’ll own features from architectural design to testing and deployment, ensuring our frontend interfaces and backend services are as performant as they are intuitive.

Beyond day-to-day feature development for our customer-facing part of the application, you will be a key contributor to company-wide strategic projects. These initiatives are designed to push the boundaries of the Sisense ecosystem, directly influencing our product roadmap and evolving how our customers integrate intelligence into their own applications.

What You’ll Do

• Build and scale end-to-end features using React for modern, responsive frontends and Node.js for high-performance backend services. You will spend the majority of your time writing clean, production-ready code that powers our core platform.
• Play a key role in the continuous evolution of our platform by maintaining and bridging functionality within our AngularJS codebase, ensuring a seamless experience as we transition toward modern frameworks.
• Take full responsibility for the lifecycle of your features. You are expected to deliver mission-critical projects at the highest quality, ensuring they are performant, robust, and timely delivered with end-to-end excellence.
• Be responsible for testing of your delivery, including manual and automated testing.
• Heavily integrate AI tools (Cursor, Claude etc.) into your daily development process to accelerate your output, optimize code performance, and stay at the forefront of engineering efficiency.
• Actively brainstorm with peers to solve technical hurdles and refine product ideas. You will work on company strategic projects that move the needle for Sisense, directly impacting our long-term product trajectory.

About You

• You have 5+ years of experience building robust applications. You are highly proficient with React, TypeScript, and Node.js (Express.js/Nest.js experience is a significant plus).
• You possess a deep understanding of modern web standards, RESTful APIs, SOLID principles and the nuances of high-performance frontend development.
• You understand CI/CD processes and can apply your skills to develop and optimize pipelines.
• You don’t just write code; you deliver well-architected, maintainable solutions. You have got a skill for breaking down complex business requirements into clear, executable technical tasks.
• You are self-driven, take full accountability for your projects from start to finish, and aim to follow the highest quality standards.
• You are passionate about efficiency and responsibly leverage AI tools to boost your personal performance and stay at the cutting edge of development practices.
• You enjoy brainstorming and solving problems with a team. Your English is at an Upper-Intermediate level (B2) or higher, allowing you to articulate technical concepts clearly.

Nice to Have

• Experience with BI/analytics tools, data-intensive applications, or building features that integrate AI/ML models.
• Hands-on exposure to cloud environments (AWS, GCP, or Azure) and containerization tools like Docker or Kubernetes.
• Familiarity with AngularJS is your advantage as we modernize our core platform.

OUR BENEFITS:

• We’re all working remotely 
• We hire only people we trust. All Sisensers join the company without a probation period
• We believe all Sisensers should be owners of our company’s success. We grant all employees stock options that start vesting on Day One
• We support a work-life balance philosophy and provide unlimited vacations (flexible time off) and additional long weekends to all Sisensers
• We support professional growth with access to the modern learning platform
• We care about each other. All team members have extended medical insurance
• We provide Sisensers with a sports reimbursement to support physical fitness and mental well-being.

Sisense is a leading AI-powered Analytics Platform as a Service (AnPaaS) that empowers product teams and developers to embed conversational, predictive, and agentic intelligence directly into applications and workflows. Our API-first, developer-first platform turns complex data into faster, smarter, actionable decisions for over 2,000 global customers across financial services, retail, healthcare, and technology.

With the recent launch of Sisense Intelligence (Intelligence Assistant, MCP server, Managed LLM), we are pushing the boundaries of embedded analytics and making AI-driven insights accessible at scale.

The Role

As a Platform Engineer, you will be a key member of one of our core engineering teams, responsible for designing, building, and evolving the foundational platform that powers Sisense’s embedded AI analytics capabilities. You will work on high-impact infrastructure, scalability, and developer experience challenges in a modern, cloud-native environment using Node.js and TypeScript.

This is a hands-on role where you’ll tackle complex technical problems, influence architectural decisions, and help shape the future of our developer platform.

Key Responsibilities

• Design, develop, and maintain core platform components using Node.js, Java and TypeScript.
• Work closely with architects and cross-functional teams to build scalable, reliable SaaS foundations for embedded analytics and AI features.
• Lead large and complex technical projects end-to-end, from design to production.
• Analyze and troubleshoot production systems, ensuring high availability and performance.
• Research, evaluate, and introduce new technologies and best practices to improve platform quality and developer experience.
• Mentor and guide team members, raise development standards, and contribute to a culture of technical excellence.

Requirements

• 5+ years of hands-on experience designing and developing backend applications with Node.js and TypeScript.
• Advantage : 3+ years as a Backend/Platform Engineer, with strong focus on infrastructure and SaaS platforms.
• Deep expertise in building scalable, event-driven, cloud-native architectures.
• Solid experience with the modern Node.js ecosystem (NestJS or similar frameworks is a plus).
• Strong knowledge of cloud platforms (AWS, GCP, or Azure), k8s and containerization technologies.
• Experience with monitoring, observability, and distributed systems troubleshooting.
• Excellent problem-solving, analytical, and communication skills.
• Your English is at an Upper-Intermediate level (B2) or higher, allowing you to articulate technical concepts clearly.

Nice to Have

• Experience with OpenTelemetry, monitoring tools, or distributed tracing.
• Background in data-intensive platforms, analytics, or BI systems.

OUR BENEFITS:

• We’re all working remotely.
• We hire only people we trust. All Sisensers join the company without a probation period.
• We believe all Sisensers should be owners of our company’s success. We grant all employees stock options that start vesting on Day One.
• We support a work-life balance philosophy and provide unlimited vacations (flexible time off) and additional long weekends to all Sisensers.
• We support professional growth with access to the modern learning platform.
• We care about each other. All team members have extended medical insurance.
• We provide Sisensers with a sports reimbursement to support physical fitness and mental well-being.

About Shelf

The enterprise is going agentic — but most AI agents fail when they hit real business complexity. Shelf is changing that.

We’ve built the operating system for agentic AI: a platform that models your policies, workflows, and operational logic into an AI Data Model so agents don’t just respond — they reason. The result? AI that understands how your business actually runs and delivers precise, compliant, auditable outcomes at scale.

Brands like Amazon, Nespresso, HelloFresh, and KeyBank trust Shelf to power AI agents that resolve 85% of cases autonomously, cut handle times by 20–25%, and turn hours-long processes into seconds. We’re partnered with Microsoft, Salesforce, OpenAI, Snowflake, and Databricks — and recognized by Gartner (Cool Vendor) and IDC (Innovator) for our approach.

If you want to sell the infrastructure that makes agentic AI actually work in the enterprise, you’re in the right place.

Our mission is to empower humanity with better answers everywhere.

Senior Frontend React Developer:

As a Frontend Engineer at Shelf, you'll craft the interfaces that make enterprise AI accessible and trustworthy. While others are building chatbots, we're solving the harder problem: how do you build UIs that help users confidently navigate AI-powered systems processing millions of documents, while maintaining enterprise-grade reliability?

You won't just build React components — you'll architect production-ready Next.js applications that handle high-load scenarios with complex states, real-time AI streaming, and multiple layers of enterprise functionality. Every interface decision you make directly impacts how knowledge workers at the biggest companies in the market interact with their most critical information.

This is frontend engineering at its most demanding. You'll tackle challenges like building real-time streaming interfaces for LLM responses, architecting state management for concurrent AI operations across multiple tenants, creating accessible interfaces for complex knowledge graphs with thousands of nodes, and ensuring blazing fast interactions even with petabytes of searchable content. Your components will bridge everything from enterprise authentication systems to cutting-edge AI models, requiring both sophisticated technical skills and sharp product instincts.

We obsess over frontend quality because we're building the trust layer for AI itself. When your interfaces gracefully handle edge cases, provide clear feedback during AI processing, and remain performant under load, you're not just meeting UX standards - you're directly enabling users to trust AI-powered answers and make critical business decisions with confidence.

You'll work on production SSR applications serving thousands of enterprise users, implementing localization for global markets, ensuring accessibility compliance, and maintaining security standards that pass SOC 2 audits. Your code will integrate with our Elasticsearch clusters, DynamoDB tables, and Aurora PostgreSQL databases through the largest park of REST APIs, handling real-time websocket updates for AI streaming and collaborative features.

We're a product company that ships fast without compromising on lasting quality. You'll work alongside proactive, ever-learning engineers who actively use AI coding assistants (OpenAI Codex, Claude Code) to accelerate development. We build custom MCP servers, implement DSPy pipelines for LLM optimization, and experiment with different AI tools for implementation. In our environment, AI isn't just what we build — it's how we build.

The best engineers we know are drawn to problems that matter. If you're excited by the challenge of building interfaces that make the AI revolution actually usable and trustworthy for enterprise users, this role offers the rare combination of technical depth, meaningful impact, and the prestige of solving UX patterns that the industry hasn't figured out yet.

Responsibilities

• Design and implement production-ready Next.js SSR applications with complex state management, handling high-load scenarios and real-time AI interactions at scale
• Build interfaces for AI-powered features including streaming LLM responses, semantic search across millions of documents, interactive knowledge graphs, intelligent content recommendations, and AI agentic builders
• Architect component libraries and maintain our design system in Storybook, ensuring reusability, accessibility, and consistent UX patterns across the platform
• Develop enterprise-grade functionality including multi-language support, accessibility compliance, cross-browser compatibility, and security implementations that meet SOC 2 standards
• Create comprehensive technical specifications and component API designs that clearly communicate interface decisions, performance trade-offs, and accessibility considerations
• Build and optimize data-heavy UIs using React Flow for node-based graphs, Highcharts for analytics visualizations, and custom virtualization for handling large datasets
• Instrument components for performance monitoring, track Core Web Vitals, implement error boundaries, and build automated visual regression tests with Playwright
• Take full ownership of the features you build, monitoring their performance in production, optimizing bundle sizes, and ensuring they scale gracefully as user load grows
• Work with SWR for intelligent data fetching, caching, and revalidation strategies that minimize API calls while keeping UIs responsive and data fresh
• Integrate with backend services via REST APIs, handle websocket connections for real-time updates, and implement optimistic UI patterns for seamless user experiences
• Leverage AI coding assistants to accelerate development while maintaining high code quality, and contribute to building internal AI agents that automate frontend workflows
• Stay current with React ecosystem best practices, Next.js updates, AI UX patterns, and modern frontend architecture—experiment with new approaches and share findings with the team
• Contribute to our engineering standards and practices through thoughtful code reviews, mentor colleagues on frontend best practices, and actively participate in our culture of continuous learning

Requirements

• Over 5 years of professional frontend engineering experience, including more than 3 years specializing in React and modern JavaScript/TypeScript
• Production Next.js experience - you've built and shipped SSR applications at scale, understand app router patterns, server components, and the trade-offs between SSR, SSG, and CSR
• Deep TypeScript expertise - you write type-safe code with generics, utility types, and advanced patterns. 
• Complex state management - hands-on experience architecting state solutions for challenging scenarios: real-time collaboration, optimistic updates, multi-tenant data isolation, and large-scale data synchronization
• Enterprise application development - you've built applications with localization (i18n), accessibility, security best practices, and compliance requirements. You understand the complexity beyond "making it work"
• AI/LLM interface experience - you've built interfaces for AI-powered features: streaming token responses, chat UIs, semantic search, or similar real-time AI interactions
• High-load optimization - proven track record optimizing applications for performance under heavy traffic, large datasets, and concurrent operations. You monitor Core Web Vitals and know how to improve them
• Modern CSS mastery - strong expertise with Tailwind CSS and/or CSS-in-JS solutions. You can implement pixel-perfect designs while maintaining responsive layouts and dark mode support
• Write well-structured, testable code with thoughtful component abstractions and clean APIs. You know when to abstract and when to keep it simple
• Strong problem-solving skills and genuine curiosity - you don't wait for designs to be perfect but proactively identify UX issues and propose solutions. You're never satisfied with "good enough" and constantly refine your craft
• Experience with AI coding assistants (OpenAI Codex, Claude, etc.) and eagerness to push the boundaries of AI-assisted development. Part of this role involves creating AI agents to automate portions of the frontend workflow
• Familiarity with observability and monitoring tools like Datadog, Sentry, or similar platforms for tracking frontend performance and errors in production
• Upper-Intermediate or better English skills for technical communication, documentation, and collaborating with distributed teams
• Present your work effectively both verbally and visually - you can articulate design decisions, create component documentation, and explain technical trade-offs clearly

Be a Plus:

• Experience with React Flow, Highcharts, or other complex data visualization libraries
• Understanding of Node.js/Python/backend fundamentals - you can read backend code and contribute to API design discussions
• Experience with SWR, React Query, or similar data fetching libraries
• Hands-on experience with vector search UIs, RAG interfaces, or semantic search implementations
• Familiarity with MCP (Model Context Protocol), DSPy, or other cutting-edge AI frameworks
• Experience with monorepo tools (Lerna, Turborepo, Nx) and managing shared component libraries
• AWS services knowledge (S3, CloudFront, Lambda) and understanding of serverless architectures
• Built or contributed to design systems or open-source component libraries
• Experience with Playwright, Puppeteer, or Cypress for comprehensive E2E testing
• Experience building AI agent interfaces or agentic AI workflows

What Shelf Offers:

• B2B contract
• Company Stock Options
• Hardware: MacBook Pro
• Modern technical stack. Develop open-source software
• Premier AI development environment: GitHub Copilot, Claude Code, OpenAI Codex, TypingMind, v0, MCP Servers, plus credits for experimenting with emerging AI tools

Why Shelf

• Our Leadership Team has deep knowledge management and AI domain expertise and enterprise SaaS background to execute this plan
• We love our customers and our customers love us. Ask a Shelf customer why, and they’ll tell you it’s because of our innovative capabilities, rock-solid reliability, they truly enjoy working with our people, but most of all – it’s the improvements they see in their business KPIs.
• We have raised over $60 million in funding and our investors include Tiger Global, Insight Partners, Connecticut Innovations, and others
• We have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a row
• We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few months

Our Values:

Quality - We’re united by our focus on world‑class Quality. Quality in all things – starting with everything that leaves your desk. Everything you touch – every email, report, campaign, and piece of code – should be outstanding. Your work product should blow people away. Having people look at what you’ve done and say, “Wow.” That’s the standard here. Remember that how you do anything is how you do everything. Focus on craftsmanship—your ability to make things better.

Momentum - for us means that you should know that the things you’re responsible for are moving forward. When you look around and see something that’s stalled, get it moving again. We pride ourselves on “ball movement.” When your boss or team leaves you with something, they should return to see measurable progress. Small, continuous movement is our recipe for success. Constantly look for how to make the work around you move forward. We want you to initiate solutions, ideas, and progress. Don’t wait for it to come to you—reach out and create movement. All the time.

Accountability - We expect every team member to feel that they are accountable for more than anyone might normally expect. Each of us should feel real responsibility for things even at the edge of our control. We consistently share and align on expectations, give each other open and respectful feedback, and use those two drivers to ensure that every agreement we make with one another is clear and complete.

Hard Work - We’re here to do something difficult together. We care intensely about the mission and we expect that from our teammates. That care means that we work hard here. Hard work comes with long hours, extra effort…and real opportunity at Shelf. Your passion for creating and sustaining output is a part of our DNA. Support each other, cheer each other on, drive the mission forward. Great teams sustain intense effort together to win.

Learning Agility - We’re innovating in one of the fastest‑moving spaces in history at a time of accelerating global change. That’s incredibly exciting and requires each of us to commit fully to learning each and every day so that we can be the best at what we do. None of us know everything. All of us can learn anything. Staying open and constantly curious is a key success driver at Shelf. It also requires humility. We prize people who are consistently humble and open to making mistakes and growing from them. Recognize also that learning itself is a skill…we need you to be really good at it. Keep dialing in your own understanding about how you learn best and push yourself to keep growing.

Adapt and Thrive - Overcoming challenges lives deep in our DNA. We have a proud history of understanding and living the reality that obstacles are our opportunities…they’re the key to our success. Change is a constant in our business and fighting change is counterproductive. We need you to be good at being uncomfortable and understand that discomfort is the key to growth. Cultivate your own ability to adapt and know that struggling well is something you’ll share with every team you’re on at Shelf. Our company stories are about thriving through real difficulty…together.

Win Together - We win or lose as a team. Always. Everything you do here is connected to the rest of the organization. Part of our shared team environment demands full honesty…real candor and directness with one another. We expect you to constantly be thinking about how to support your teammates and the company, always acting in service to our shared mission and what’s best for the organization as a whole.

About Shelf

The enterprise is going agentic — but most AI agents fail when they hit real business complexity. Shelf is changing that.

We’ve built the operating system for agentic AI: a platform that models your policies, workflows, and operational logic into an AI Data Model so agents don’t just respond — they reason. The result? AI that understands how your business actually runs and delivers precise, compliant, auditable outcomes at scale.

Brands like Amazon, Nespresso, HelloFresh, and KeyBank trust Shelf to power AI agents that resolve 85% of cases autonomously, cut handle times by 20–25%, and turn hours-long processes into seconds. We’re partnered with Microsoft, Salesforce, OpenAI, Snowflake, and Databricks — and recognized by Gartner (Cool Vendor) and IDC (Innovator) for our approach.

If you want to sell the infrastructure that makes agentic AI actually work in the enterprise, you’re in the right place.

Our mission is to empower humanity with better answers everywhere.

Summary

The R&D department plays a pivotal role in driving Shelf to disrupt the market. We are looking for Machine Learning experts that are able to deliver end to end with a blend of experience: Python engineering, ML engineering, and pragmatic Data science and Machine learning research. You will ship end-to-end features—from problem framing and experimentation to service deployment, and ongoing operations—quickly and with high quality. Your work will power ML- and LLM-driven services used by top enterprises like Amazon, Mayo Clinic, AmFam, and Nespresso.

This role requires strong Python engineering capabilities coupled with a strong ability to deliver robust ML solutions, along with ML research literacy to choose sound methodologies, define metrics, and evaluate different approaches effectively.

You’ll work in an agile environment, move fast, and own what you ship.

Responsibilities

• Own end-to-end delivery: ideate, research, prototype, productionize, and operate ML-powered services with an expectation to iterate and ship frequently
• Stand up robust training/evaluation pipelines: dataset curation, labeling/feedback loops, experiment tracking, offline/online metrics, and A/B testing
• Solve problems using sound methodology, evaluate approaches along with 
• Transform ML models and LLM workflows (including RAG) into reusable, versioned, observable production services with CI/CD
• Collaborate with Product Owners to shape our product and requirements
• Conduct and receive code reviews; champion engineering excellence, testing discipline, and documentation
• Leverage AI coding assistants to accelerate development and create internal agents that automate parts of the engineering workflow
• Share learnings through demos, docs, and knowledge sessions; contribute to a culture of continuous improvement

Requirements

• 3+ years of professional experience researching and shipping ML-based solutions, with strong Python skills and a track record of delivering fast without sacrificing quality
• Proven experience in owning research problems end-to-end, starting from initial data analysis, through iterative research phases to delivering on production
• Practical NLP/LLM experience: transformers, embeddings, prompt design, and evaluation; ability to choose and justify metrics and methodologies
• Strong backend fundamentals: designing RESTful services, schema design, data modeling, and performance tuning for SQL and NoSQL stores
• Data processing skills: pandas/NumPy; experience with batch/stream processing and ETL orchestration (e.g., Airflow, Step Functions)
• Strong English verbal and written communication

As a plus

• LLM ops and safety: eval frameworks (e.g., RAGAS), guardrails, red-teaming, prompt optimization at scale
• Model optimization: quantization, distillation, pruning; GPU/accelerator-aware serving
• Experience with AWS ML stack (SageMaker, Batch, Step Functions, Lambda, SQS/SNS, DynamoDB, ECS, EC2, S3)
• Vector databases and search: Pinecone, Elasticsearch, pgvector, FAISS, or DeepLake
• Background in reinforcement learning, agent frameworks, or autonomous agents
• Publications, open-source contributions, GitHub portfolio

What Shelf Offers

• B2B contract
• Company Stock Options
• Hardware: MacBook Pro
• Modern technical stack. Develop open-source software
• Premier AI development environment: GitHub Copilot, Claude Code, OpenAI, TypingMind, v0, MCP Servers, plus credits to experiment with emerging AI tools

Why Shelf

• Our Leadership Team has deep knowledge management and AI domain expertise and enterprise SaaS background to execute this plan
• We love our customers and our customers love us. Ask a Shelf customer why, and they’ll tell you it’s because of our innovative capabilities, rock-solid reliability, they truly enjoy working with our people, but most of all – it’s the improvements they see in their business KPIs.
• We have raised over $60 million in funding and our investors include Tiger Global, Insight Partners, Connecticut Innovations, and others
• We have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a row
• We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few months

Our Values:

Quality - We’re united by our focus on world‑class Quality. Quality in all things – starting with everything that leaves your desk. Everything you touch – every email, report, campaign, and piece of code – should be outstanding. Your work product should blow people away. Having people look at what you’ve done and say, “Wow.” That’s the standard here. Remember that how you do anything is how you do everything. Focus on craftsmanship—your ability to make things better.

Momentum - for us means that you should know that the things you’re responsible for are moving forward. When you look around and see something that’s stalled, get it moving again. We pride ourselves on “ball movement.” When your boss or team leaves you with something, they should return to see measurable progress. Small, continuous movement is our recipe for success. Constantly look for how to make the work around you move forward. We want you to initiate solutions, ideas, and progress. Don’t wait for it to come to you—reach out and create movement. All the time.

Accountability - We expect every team member to feel that they are accountable for more than anyone might normally expect. Each of us should feel real responsibility for things even at the edge of our control. We consistently share and align on expectations, give each other open and respectful feedback, and use those two drivers to ensure that every agreement we make with one another is clear and complete.

Hard Work - We’re here to do something difficult together. We care intensely about the mission and we expect that from our teammates. That care means that we work hard here. Hard work comes with long hours, extra effort…and real opportunity at Shelf. Your passion for creating and sustaining output is a part of our DNA. Support each other, cheer each other on, drive the mission forward. Great teams sustain intense effort together to win.

Learning Agility - We’re innovating in one of the fastest‑moving spaces in history at a time of accelerating global change. That’s incredibly exciting and requires each of us to commit fully to learning each and every day so that we can be the best at what we do. None of us know everything. All of us can learn anything. Staying open and constantly curious is a key success driver at Shelf. It also requires humility. We prize people who are consistently humble and open to making mistakes and growing from them. Recognize also that learning itself is a skill…we need you to be really good at it. Keep dialing in your own understanding about how you learn best and push yourself to keep growing.

Adapt and Thrive - Overcoming challenges lives deep in our DNA. We have a proud history of understanding and living the reality that obstacles are our opportunities…they’re the key to our success. Change is a constant in our business and fighting change is counterproductive. We need you to be good at being uncomfortable and understand that discomfort is the key to growth. Cultivate your own ability to adapt and know that struggling well is something you’ll share with every team you’re on at Shelf. Our company stories are about thriving through real difficulty…together.

Win Together - We win or lose as a team. Always. Everything you do here is connected to the rest of the organization. Part of our shared team environment demands full honesty…real candor and directness with one another. We expect you to constantly be thinking about how to support your teammates and the company, always acting in service to our shared mission and what’s best for the organization as a whole.

The landscape of AI is evolving rapidly, and PandaDoc is investing heavily in machine learning to power the next generation of intelligent document workflows. Our goal is to build scalable, production-grade AI systems that automate document understanding, extract structured data at scale, and enable new AI-first product experiences for tens of thousands of businesses.

As an ML Engineer focused on Document Intelligence and GenAI, you will design, train, evaluate, and optimize models that transform unstructured documents into high-quality structured data. You’ll work across the full stack of model development—datasets, training, inference, deployment pipelines—and help bring cutting-edge research into real production systems at scale.

What makes this role unique?

• Document Intelligence at Scale: Your work will directly power PandaDoc’s core AI capabilities—from layout detection and OCR to structured extraction, retrieval, and document-based reasoning.
• High Ownership, High Impact: You will design end-to-end ML systems, influence roadmap decisions, and work closely with product, engineering, and design to define requirements and ship production AI features.
• Real-World ML Challenges: You’ll tackle model robustness, evaluation, latency, observability, RAG quality, model routing, and the complexities of deploying AI systems that must perform reliably on millions of documents.
• Deep GenAI Integration: You’ll experiment with frontier and open-source models, integrate vision–language systems, and build efficient pipelines for inference, guardrails, fine-tuning, and document-aware reasoning.

In this role, you will:

• Model Development & Evaluation
  • Build and maintain evaluation frameworks for document models, LLMs, OCR, and structured extraction.
  • Define metrics, benchmarks, and validation strategies for real-world document workloads.
• Dataset & Pipeline Creation
  • Design and curate high-quality datasets for supervised training, fine-tuning, and validation.
  • Create scalable preprocessing pipelines for PDFs, scans, images, forms, and semi-structured documents.
• Model Training & Fine-Tuning
  • Train and fine-tune transformer-based OCR, VLMs, layout models, and open-source LLMs for document understanding tasks.
  • Optimize models for reliability, accuracy, and cost efficiency in production environments.
• Inference & Deployment
  • Deploy ML models with modern inference runtimes (vLLM, TGI, TensorRT, ONNX Runtime).
  • Build guardrails, monitoring, and fallback mechanisms to ensure safe and predictable model behavior.
• RAG & Document Reasoning
  • Develop retrieval and chunking strategies tailored to document structures (tables, forms, multi-page PDFs).
  • Optimize end-to-end RAG pipelines for semantic search, Q&A, and workflow automation.
• Cross-Functional Collaboration
  • Partner with PMs, backend engineers, and product designers to define AI opportunities and translate requirements into technical solutions.

About you:

We are expanding our AI/ML function with an ML Engineer who specializes in document intelligence, vision–language models, and LLM-based extraction and reasoning. You should be comfortable with both traditional document AI approaches and cutting-edge GenAI workflows. You thrive in fast-moving environments, are self-directed, and enjoy solving practical ML problems that directly impact customers.

We’re looking for someone with experience in:

• Vision transformers, layout models, and OCR systems
• Structured extraction from complex documents
• RAG for document-heavy workloads
• Optimizing LLM pipelines for cost, accuracy, and throughput
• Deploying and benchmarking models in real production systems

Required Experience

• 5+ years of Python experience
• Experience training, fine-tuning, and deploying traditional computer vision models for document intelligence tasks (layout detection, table extraction, OCR, information extraction)
• Hands-on experience with document understanding frameworks and models:
  • Traditional document AI models (LayoutLM, Donut, DocFormer)
  • Modern vision-language models with OCR capabilities (DeepSeek-OCR, LightOnOCR-1B, etc.)
  • Experience deploying and optimizing models using inference frameworks such as vLLM (preferred), TGI, TensorRT, or ONNX Runtime
  • Experience applying LLMs to document intelligence workflows, including both frontier models and open-source alternatives
  • Strong understanding of coordinate systems and spatial reasoning for absolute positioning and field detection in forms/documents

It would be awesome if you had:

• Familiarity with PDF parsing libraries and document preprocessing pipelines
• Experience fine-tuning open-source models for domain-specific document tasks
• Knowledge of evaluation metrics for document understanding tasks (F1, exact match, etc.)

Company Overview: 

PandaDoc empowers more than 67,000 growing organizations to thrive by taking the work out of document workflow. PandaDoc provides an all-in-one document workflow automation platform that helps fast scaling teams accelerate the ability to create, manage, and sign digital documents including proposals, quotes, contracts, and more.  For more information, please visit https://www.pandadoc.com.

Company Culture: 

We're known for our work-life balance, kind co-workers, & creative virtual team-bonding events. And although our Pandas are located across the globe, we stay connected with the help of technology and ensure that everyone on our team feels, well, like a team.

Pandas work best when they're happy. We retain our talent by upholding our values of integrity & transparency, and selling a product that changes the lives of our customers. 

Check out our LinkedIn to learn more.

Benefits:

• An honest, open culture that emphasizes feedback and promotes professional and personal development
• An opportunity to work from anywhere — our team is distributed worldwide, from Lisbon to Manila, from Florida to California
• 6 self care days
• A competitive salary
• And much more!

PandaDoc is an Equal Opportunity Employer. We are committed to equal treatment of all employees without regard to race, national origin, religion, gender, age, sexual orientation, veteran status, physical or mental disability or other basis protected by law.

EXTERNAL RECRUITERS

Approval Requirement

The use of external recruiters/staffing agencies requires prior approval from our HR Team. The HR Team at PandaDoc requests that external recruiters/staffing agencies not to contact PandaDoc employees directly in an attempt to present candidates. Complying with this request will be a factor in determining future professional relationships with PandaDoc.

The landscape of AI is evolving rapidly, and PandaDoc is investing heavily in machine learning to power the next generation of intelligent document workflows. Our goal is to build scalable, production-grade AI systems that automate document understanding, extract structured data at scale, and enable new AI-first product experiences for tens of thousands of businesses.

As an ML Engineer focused on Document Intelligence and GenAI, you will design, train, evaluate, and optimize models that transform unstructured documents into high-quality structured data. You’ll work across the full stack of model development—datasets, training, inference, deployment pipelines—and help bring cutting-edge research into real production systems at scale.

What makes this role unique?

• Document Intelligence at Scale: Your work will directly power PandaDoc’s core AI capabilities—from layout detection and OCR to structured extraction, retrieval, and document-based reasoning.
• High Ownership, High Impact: You will design end-to-end ML systems, influence roadmap decisions, and work closely with product, engineering, and design to define requirements and ship production AI features.
• Real-World ML Challenges: You’ll tackle model robustness, evaluation, latency, observability, RAG quality, model routing, and the complexities of deploying AI systems that must perform reliably on millions of documents.
• Deep GenAI Integration: You’ll experiment with frontier and open-source models, integrate vision–language systems, and build efficient pipelines for inference, guardrails, fine-tuning, and document-aware reasoning.

In this role, you will:

• Model Development & Evaluation
  • Build and maintain evaluation frameworks for document models, LLMs, OCR, and structured extraction.
  • Define metrics, benchmarks, and validation strategies for real-world document workloads.
• Dataset & Pipeline Creation
  • Design and curate high-quality datasets for supervised training, fine-tuning, and validation.
  • Create scalable preprocessing pipelines for PDFs, scans, images, forms, and semi-structured documents.
• Model Training & Fine-Tuning
  • Train and fine-tune transformer-based OCR, VLMs, layout models, and open-source LLMs for document understanding tasks.
  • Optimize models for reliability, accuracy, and cost efficiency in production environments.
• Inference & Deployment
  • Deploy ML models with modern inference runtimes (vLLM, TGI, TensorRT, ONNX Runtime).
  • Build guardrails, monitoring, and fallback mechanisms to ensure safe and predictable model behavior.
• RAG & Document Reasoning
  • Develop retrieval and chunking strategies tailored to document structures (tables, forms, multi-page PDFs).
  • Optimize end-to-end RAG pipelines for semantic search, Q&A, and workflow automation.
• Cross-Functional Collaboration
  • Partner with PMs, backend engineers, and product designers to define AI opportunities and translate requirements into technical solutions.

About you:

We are expanding our AI/ML function with an ML Engineer who specializes in document intelligence, vision–language models, and LLM-based extraction and reasoning. You should be comfortable with both traditional document AI approaches and cutting-edge GenAI workflows. You thrive in fast-moving environments, are self-directed, and enjoy solving practical ML problems that directly impact customers.

We’re looking for someone with experience in:

• Vision transformers, layout models, and OCR systems
• Structured extraction from complex documents
• RAG for document-heavy workloads
• Optimizing LLM pipelines for cost, accuracy, and throughput
• Deploying and benchmarking models in real production systems

Required Experience

• 5+ years of Python experience
• Experience training, fine-tuning, and deploying traditional computer vision models for document intelligence tasks (layout detection, table extraction, OCR, information extraction)
• Hands-on experience with document understanding frameworks and models:
  • Traditional document AI models (LayoutLM, Donut, DocFormer)
  • Modern vision-language models with OCR capabilities (DeepSeek-OCR, LightOnOCR-1B, etc.)
  • Experience deploying and optimizing models using inference frameworks such as vLLM (preferred), TGI, TensorRT, or ONNX Runtime
  • Experience applying LLMs to document intelligence workflows, including both frontier models and open-source alternatives
  • Strong understanding of coordinate systems and spatial reasoning for absolute positioning and field detection in forms/documents

It would be awesome if you had:

• Familiarity with PDF parsing libraries and document preprocessing pipelines
• Experience fine-tuning open-source models for domain-specific document tasks
• Knowledge of evaluation metrics for document understanding tasks (F1, exact match, etc.)

Company Overview: 

PandaDoc empowers more than 67,000 growing organizations to thrive by taking the work out of document workflow. PandaDoc provides an all-in-one document workflow automation platform that helps fast scaling teams accelerate the ability to create, manage, and sign digital documents including proposals, quotes, contracts, and more.  For more information, please visit https://www.pandadoc.com.

Company Culture: 

We're known for our work-life balance, kind co-workers, & creative virtual team-bonding events. And although our Pandas are located across the globe, we stay connected with the help of technology and ensure that everyone on our team feels, well, like a team.

Pandas work best when they're happy. We retain our talent by upholding our values of integrity & transparency, and selling a product that changes the lives of our customers. 

Check out our LinkedIn to learn more.

Benefits:

• An honest, open culture that emphasizes feedback and promotes professional and personal development
• An opportunity to work from anywhere — our team is distributed worldwide, from Lisbon to Manila, from Florida to California
• 6 self care days
• A competitive salary
• And much more!

PandaDoc is an Equal Opportunity Employer. We are committed to equal treatment of all employees without regard to race, national origin, religion, gender, age, sexual orientation, veteran status, physical or mental disability or other basis protected by law.

EXTERNAL RECRUITERS

Approval Requirement

The use of external recruiters/staffing agencies requires prior approval from our HR Team. The HR Team at PandaDoc requests that external recruiters/staffing agencies not to contact PandaDoc employees directly in an attempt to present candidates. Complying with this request will be a factor in determining future professional relationships with PandaDoc.

The landscape of AI is evolving rapidly, and PandaDoc is investing heavily in machine learning to power the next generation of intelligent document workflows. Our goal is to build scalable, production-grade AI systems that automate document understanding, extract structured data at scale, and enable new AI-first product experiences for tens of thousands of businesses.

As an ML Engineer focused on Document Intelligence and GenAI, you will design, train, evaluate, and optimize models that transform unstructured documents into high-quality structured data. You’ll work across the full stack of model development—datasets, training, inference, deployment pipelines—and help bring cutting-edge research into real production systems at scale.

What makes this role unique?

• Document Intelligence at Scale: Your work will directly power PandaDoc’s core AI capabilities—from layout detection and OCR to structured extraction, retrieval, and document-based reasoning.
• High Ownership, High Impact: You will design end-to-end ML systems, influence roadmap decisions, and work closely with product, engineering, and design to define requirements and ship production AI features.
• Real-World ML Challenges: You’ll tackle model robustness, evaluation, latency, observability, RAG quality, model routing, and the complexities of deploying AI systems that must perform reliably on millions of documents.
• Deep GenAI Integration: You’ll experiment with frontier and open-source models, integrate vision–language systems, and build efficient pipelines for inference, guardrails, fine-tuning, and document-aware reasoning.

In this role, you will:

• Model Development & Evaluation
  • Build and maintain evaluation frameworks for document models, LLMs, OCR, and structured extraction.
  • Define metrics, benchmarks, and validation strategies for real-world document workloads.
• Dataset & Pipeline Creation
  • Design and curate high-quality datasets for supervised training, fine-tuning, and validation.
  • Create scalable preprocessing pipelines for PDFs, scans, images, forms, and semi-structured documents.
• Model Training & Fine-Tuning
  • Train and fine-tune transformer-based OCR, VLMs, layout models, and open-source LLMs for document understanding tasks.
  • Optimize models for reliability, accuracy, and cost efficiency in production environments.
• Inference & Deployment
  • Deploy ML models with modern inference runtimes (vLLM, TGI, TensorRT, ONNX Runtime).
  • Build guardrails, monitoring, and fallback mechanisms to ensure safe and predictable model behavior.
• RAG & Document Reasoning
  • Develop retrieval and chunking strategies tailored to document structures (tables, forms, multi-page PDFs).
  • Optimize end-to-end RAG pipelines for semantic search, Q&A, and workflow automation.
• Cross-Functional Collaboration
  • Partner with PMs, backend engineers, and product designers to define AI opportunities and translate requirements into technical solutions.

About you:

We are expanding our AI/ML function with an ML Engineer who specializes in document intelligence, vision–language models, and LLM-based extraction and reasoning. You should be comfortable with both traditional document AI approaches and cutting-edge GenAI workflows. You thrive in fast-moving environments, are self-directed, and enjoy solving practical ML problems that directly impact customers.

We’re looking for someone with experience in:

• Vision transformers, layout models, and OCR systems
• Structured extraction from complex documents
• RAG for document-heavy workloads
• Optimizing LLM pipelines for cost, accuracy, and throughput
• Deploying and benchmarking models in real production systems

Required Experience

• 5+ years of Python experience
• Experience training, fine-tuning, and deploying traditional computer vision models for document intelligence tasks (layout detection, table extraction, OCR, information extraction)
• Hands-on experience with document understanding frameworks and models:
  • Traditional document AI models (LayoutLM, Donut, DocFormer)
  • Modern vision-language models with OCR capabilities (DeepSeek-OCR, LightOnOCR-1B, etc.)
  • Experience deploying and optimizing models using inference frameworks such as vLLM (preferred), TGI, TensorRT, or ONNX Runtime
  • Experience applying LLMs to document intelligence workflows, including both frontier models and open-source alternatives
  • Strong understanding of coordinate systems and spatial reasoning for absolute positioning and field detection in forms/documents

It would be awesome if you had:

• Familiarity with PDF parsing libraries and document preprocessing pipelines
• Experience fine-tuning open-source models for domain-specific document tasks
• Knowledge of evaluation metrics for document understanding tasks (F1, exact match, etc.)

Company Overview: 

PandaDoc empowers more than 67,000 growing organizations to thrive by taking the work out of document workflow. PandaDoc provides an all-in-one document workflow automation platform that helps fast scaling teams accelerate the ability to create, manage, and sign digital documents including proposals, quotes, contracts, and more.  For more information, please visit https://www.pandadoc.com.

Company Culture: 

We're known for our work-life balance, kind co-workers, & creative virtual team-bonding events. And although our Pandas are located across the globe, we stay connected with the help of technology and ensure that everyone on our team feels, well, like a team.

Pandas work best when they're happy. We retain our talent by upholding our values of integrity & transparency, and selling a product that changes the lives of our customers. 

Check out our LinkedIn to learn more.

Benefits:

• An honest, open culture that emphasizes feedback and promotes professional and personal development
• An opportunity to work from anywhere — our team is distributed worldwide, from Lisbon to Manila, from Florida to California
• 6 self care days
• A competitive salary
• And much more!

PandaDoc is an Equal Opportunity Employer. We are committed to equal treatment of all employees without regard to race, national origin, religion, gender, age, sexual orientation, veteran status, physical or mental disability or other basis protected by law.

EXTERNAL RECRUITERS

Approval Requirement

The use of external recruiters/staffing agencies requires prior approval from our HR Team. The HR Team at PandaDoc requests that external recruiters/staffing agencies not to contact PandaDoc employees directly in an attempt to present candidates. Complying with this request will be a factor in determining future professional relationships with PandaDoc.