# Senior Forward Deployed Engineer **Company:** [UiPath](https://scaleengineer.com/companies/uipath) A Senior Forward Deployed Engineer role at UiPath where you'll design, build, and deploy production-grade LLM-powered applications and multi-agent AI workflows directly with enterprise customers. This highly technical, customer-facing position requires 5-8+ years of software engineering experience with strong Python/TypeScript skills and hands-on production AI systems expertise to translate complex business problems into scalable automation solutions. **Role:** Senior Forward Deployed Engineer **Seniority:** Senior **Locations:** Bellevue **Salary:** 180000–230000 USD [Apply](https://jobs.ashbyhq.com/uipath/fd84fcf2-01c1-4da8-97c9-2641d179e250) Canonical: https://scaleengineer.com/jobs/uipath/senior-forward-deployed-engineer-fd84fcf2 --- ## Responsibilities - Design and Deploy LLM-Powered Production Systems: Build and deploy end-to-end LLM-powered applications and multi-agent AI workflows in production environments, managing the complete lifecycle from prototype through production optimization and iteration cycles. - Architect Integrated Enterprise Solutions: Design complex, end-to-end solutions that seamlessly integrate APIs, legacy enterprise systems, and modern data platforms to solve high-value business automation challenges. - Drive Customer-Centric Technical Delivery: Partner directly with enterprise customers to translate ambiguous business requirements into clearly defined, scalable AI-powered solutions while maintaining strong technical communication throughout engagement. - Own Full Delivery Responsibility: Take ownership of solution delivery from initial concept exploration and prototype development through production deployment, monitoring, optimization, and iterative improvements based on real-world performance metrics. - Optimize System Performance and Cost: Continuously optimize deployed systems for performance efficiency, operational cost reduction, and high-availability reliability standards required in enterprise production environments. - Contribute Strategic Product Insights: Distill real-world customer feedback and hands-on deployment experience into reusable architectural patterns and product recommendations that influence UiPath's platform direction and capabilities. ## Requirements ### education - {"name":"Computer Science Foundation","description":"Strong foundational knowledge in computer science fundamentals including algorithms, data structures, systems design, and software architecture principles essential for complex technical decision-making."} - {"name":"Advanced Degree (Preferred)","description":"Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field strongly preferred; demonstrates advanced technical depth and research capability in cutting-edge domains."} ### technical - {"name":"Production LLM Systems Development","description":"Demonstrated hands-on experience building, deploying, and maintaining LLM-powered applications and multi-agent systems in production environments with proven track record of system reliability and performance optimization."} - {"name":"Python and TypeScript Proficiency","description":"Strong production-level coding skills in Python and/or TypeScript with ability to write clean, maintainable, scalable code and comfortable navigating polyglot environments across multiple technology stacks."} - {"name":"Advanced Prompt Engineering","description":"Applied expertise in prompt engineering, LLM fine-tuning strategies, and techniques for optimizing model outputs in production systems including understanding of token economics and cost optimization."} - {"name":"Complex Systems Integration","description":"Proven ability to design and implement complex, highly integrated systems that combine multiple services, APIs, data platforms, and third-party tools while managing intricate system dependencies and data flow."} - {"name":"Distributed Systems Architecture","description":"Understanding of distributed systems principles, asynchronous processing patterns, scalability constraints, and architectural trade-offs relevant to AI-powered microservice environments."} - {"name":"API Design and Integration","description":"Proficiency with RESTful API design, GraphQL patterns, webhook implementations, and expertise integrating with multiple API-based services including LLM providers (OpenAI, Anthropic, Google Gemini, Claude)."} - {"name":"Cloud and Infrastructure Knowledge","description":"Practical experience deploying and managing applications on cloud platforms (AWS, Azure, GCP) with understanding of containerization, orchestration, monitoring, and production-grade infrastructure patterns."} ### experience - {"name":"5-8+ Years Software Engineering","description":"Minimum 5-8 years of professional software engineering experience with demonstrated progression from foundational to advanced technical responsibilities, preferably including customer-facing or applied engineering work."} - {"name":"Production AI/ML Systems (Preferred)","description":"Substantial hands-on experience building and deploying machine learning models, AI systems, or automation platforms in production environments with measurable business impact and operational excellence."} - {"name":"Agent Frameworks and Orchestration (Preferred)","description":"Practical experience with agent frameworks, orchestration systems (Kubernetes, workflow engines), distributed computing patterns, or multi-agent system architectures."} - {"name":"Startup or Consulting Environment (Preferred)","description":"Background working in fast-paced startup environments, consulting-driven delivery roles, or forward-deployed technical positions requiring rapid context-switching and execution under ambiguity."} ## Skills ### required - {"name":"Python","description":"Advanced Python development for production systems, data processing, and AI application development with familiarity of modern Python frameworks and libraries."} - {"name":"TypeScript","description":"Strong TypeScript and JavaScript expertise for building scalable full-stack applications, particularly in Node.js environments and AI-powered backend services."} - {"name":"LLM Platforms and APIs","description":"Hands-on experience integrating with major LLM providers including OpenAI GPT models, Anthropic Claude, Google Gemini, and Hugging Face with understanding of model selection criteria and cost optimization."} - {"name":"Prompt Engineering","description":"Applied expertise in crafting effective prompts, engineering few-shot examples, managing context windows, and optimizing prompts for specific use cases and models."} - {"name":"Systems Design","description":"Ability to design scalable, maintainable system architectures that handle complex requirements, asynchronous workflows, and integration with enterprise systems."} - {"name":"Problem-Solving Under Ambiguity","description":"Demonstrated ability to take ill-defined customer problems, decompose them into technical requirements, and rapidly prototype and iterate solutions in production."} - {"name":"Stakeholder Communication","description":"Clear communication skills bridging technical complexity and business objectives with ability to articulate technical decisions to both engineering teams and non-technical business stakeholders."} ### preferred - {"name":"Agent Framework Expertise","description":"Practical experience with agent frameworks such as LangChain, AutoGen, Semantic Kernel, or building custom agentic systems with multi-step reasoning and tool orchestration."} - {"name":"Workflow Orchestration","description":"Experience with workflow orchestration platforms like Apache Airflow, Temporal, or cloud-native workflow engines for managing complex, multi-step automation pipelines."} - {"name":"Kubernetes and Container Architecture","description":"Hands-on experience containerizing applications with Docker and deploying/managing systems on Kubernetes for production environments."} - {"name":"Applied Machine Learning","description":"Background in applied ML including model selection, training optimization, evaluation metrics, and production ML operations (MLOps) practices."} - {"name":"Enterprise Integration Patterns","description":"Familiarity with enterprise integration patterns, middleware solutions, API gateways, and strategies for integrating with legacy systems."} - {"name":"Performance Optimization","description":"Track record optimizing system performance, reducing latency, managing costs in cloud environments, and implementing efficient resource utilization."} - {"name":"Robotic Process Automation (RPA)","description":"Prior experience with RPA platforms, business process automation, or workflow automation systems that complement AI-powered solutions."} ## Tech stack ### tools - {"name":"OpenAI API","description":"Primary LLM provider integration for accessing GPT-4, GPT-3.5-turbo, and other models for production AI applications."} - {"name":"Anthropic Claude","description":"Advanced LLM provider offering Claude models with strong reasoning capabilities for complex agentic workflows."} - {"name":"Google Gemini","description":"Google's multimodal LLM platform providing alternative model choices and integration capabilities."} - {"name":"Docker","description":"Containerization platform for packaging applications and ensuring consistent deployment across environments."} - {"name":"Kubernetes","description":"Container orchestration system for managing deployed applications, scaling, and ensuring high availability."} - {"name":"Git / GitHub","description":"Version control and collaborative development platform for managing code and coordinating with team members."} - {"name":"Postman","description":"API development and testing tool for iterating on API integrations during development and deployment."} - {"name":"AWS / Azure / Google Cloud","description":"Major cloud platforms for deploying, scaling, and managing production AI applications with global distribution."} - {"name":"CI/CD Pipelines (GitHub Actions, GitLab CI)","description":"Continuous integration and deployment tools for automating testing, building, and deploying applications."} - {"name":"Monitoring and Logging (Datadog, New Relic, ELK Stack)","description":"Observability platforms for monitoring system performance, tracking errors, and maintaining production system reliability."} ### others - {"name":"Prompt Engineering Techniques","description":"Advanced prompt design methodologies including few-shot learning, chain-of-thought prompting, and prompt optimization for specific LLM models."} - {"name":"Retrieval-Augmented Generation (RAG)","description":"Techniques for combining LLMs with document retrieval systems to ground AI outputs in enterprise knowledge bases and real data."} - {"name":"Multi-Agent Systems Architecture","description":"Architectural patterns for designing systems where multiple autonomous agents coordinate to accomplish complex objectives through communication and task delegation."} - {"name":"API Integration Patterns","description":"Best practices for integrating with REST/GraphQL APIs, handling rate limiting, error recovery, and building resilient API clients."} - {"name":"Agentic AI Workflows","description":"Design and implementation of autonomous AI agents capable of planning, tool usage, error handling, and iterative problem-solving."} - {"name":"Cost Optimization Strategies","description":"Techniques for optimizing LLM API costs through efficient prompt design, model selection, caching strategies, and batch processing."} ### databases - {"name":"PostgreSQL","description":"Production-grade relational database for structured data, vector storage extensions, and enterprise system integration."} - {"name":"MongoDB","description":"NoSQL database for flexible document storage, particularly useful for storing conversation histories and unstructured AI outputs."} - {"name":"Vector Databases (Pinecone, Weaviate, Milvus)","description":"Specialized databases for storing and retrieving vector embeddings essential for semantic search and RAG (Retrieval-Augmented Generation) implementations."} - {"name":"Redis","description":"In-memory data store for caching, session management, and high-performance data retrieval in AI applications."} ### languages - {"name":"Python","description":"Primary backend language for AI application development, data processing, and system scripting in production AI systems."} - {"name":"TypeScript","description":"Full-stack development language for Node.js backends and modern JavaScript-based AI application development."} - {"name":"JavaScript","description":"Frontend and backend development for creating interactive applications and integrating with web-based AI services."} ### frameworks - {"name":"LangChain","description":"Leading framework for building LLM-powered applications with chain orchestration, prompt management, and agent capabilities."} - {"name":"Semantic Kernel","description":"Microsoft's orchestration framework for connecting LLMs to various services and managing agentic workflows."} - {"name":"AutoGen","description":"Multi-agent conversation framework for building systems where agents collaborate to solve complex problems through dialogue."} - {"name":"FastAPI","description":"Modern Python web framework for building high-performance production APIs that serve AI-powered applications."} - {"name":"Node.js / Express","description":"JavaScript runtime and web framework for building scalable backend services integrating with LLM APIs."} - {"name":"React","description":"Frontend framework for building interactive user interfaces that consume AI-powered backend services."} ## Benefits ### benefits - {"name":"Comprehensive Health Coverage","description":"Medical, dental, and vision insurance plans with employer contributions covering employees and eligible dependents."} - {"name":"Equity and Stock Options","description":"Participation in UiPath's stock option program, allowing you to benefit from company growth and success as a shareholder."} - {"name":"Competitive Retirement Benefits","description":"401(k) retirement savings plan with employer matching contributions to support long-term financial planning."} - {"name":"Professional Development Budget","description":"Annual learning and development budget for conferences, courses, certifications, and tools to advance technical skills and industry knowledge."} - {"name":"Remote and Flexible Work","description":"Flexible work arrangements with ability to work hybrid or remote depending on role requirements and business needs, complemented by collaborative office spaces."} - {"name":"Generous Paid Time Off","description":"Comprehensive paid time off including vacation days, sick leave, and company holidays to maintain work-life balance and wellness."} - {"name":"Mental Health and Wellness Programs","description":"Access to mental health services, wellness programs, fitness benefits, and employee assistance programs supporting holistic well-being."} - {"name":"Parental Leave","description":"Paid parental leave policies supporting employees during life transitions and family growth."} - {"name":"Technology and Equipment","description":"Latest laptops, development hardware, and software tools provided to optimize productivity and technical capabilities."} - {"name":"Diversity and Inclusion Initiatives","description":"Active commitment to diverse and inclusive workplace with employee resource groups, mentorship programs, and equitable advancement opportunities."} ## Compensation - **max:** 240000 - **min:** 160000 - **currency:** USD - **stockOptions:** true ## Interview process ### steps - {"name":"Initial Screening Call with Recruiter","description":"Preliminary 30-minute conversation with UiPath recruiter to assess background alignment, clarify role expectations, compensation alignment, and logistics including potential travel requirements and location flexibility."} - {"name":"Technical Phone Screen","description":"1-hour technical assessment with senior engineer covering systems design fundamentals, LLM/AI concepts, Python or TypeScript coding problem, and discussion of relevant production AI system experiences."} - {"name":"Take-Home Technical Challenge","description":"Practical coding assignment (2-4 hours) to design and implement an AI-powered system component—typically involving API integration, prompt engineering, or system architecture decisions relevant to FDE responsibilities."} - {"name":"Whiteboard System Design Interview","description":"90-minute session with engineering leader to discuss complex system architecture problem, evaluate design thinking for distributed systems, integration challenges, and handling production requirements at scale."} - {"name":"Customer Scenario Discussion","description":"Conversation with current Forward Deployed Engineer or customer-facing team member exploring how you'd approach ambiguous customer problems, manage stakeholder expectations, and navigate real-world deployment constraints."} - {"name":"Leadership and Values Interview","description":"Final round with hiring manager assessing cultural fit, problem-solving approach under ambiguity, collaborative working style, and alignment with UiPath's mission-driven values and customer obsession."} - {"name":"Offer Stage and Reference Checks","description":"Reference checks and final offer discussion including compensation, equity package, start date, and onboarding logistics."} ## Full description # **Life at UiPath** The people at UiPath believe in the transformative power of automation to change how the world works. We’re committed to creating category-leading enterprise software that unleashes that power. To make that happen, we need people who are curious, self-propelled, generous, and genuine. People who love being part of a fast-moving, fast-thinking growth company. And people who care—about each other, about UiPath, and about our larger purpose. Could that be you? **About the Role** UiPath is redefining enterprise automation with AI. As a **Senior Forward Deployed Engineer (FDE)**, you’ll work directly with customers to design and deploy **agentic, AI-powered workflows** that transform how businesses operate. This is a highly technical, customer-facing role for engineers who enjoy building in real-world environments. You’ll take ambiguous problems, turn them into production systems, and see your work deliver immediate, measurable impact. If you like operating at the intersection of **AI engineering, systems design, and customer impact**, this role is built for you. **What You’ll Do** * Build and deploy **LLM-powered applications and multi-agent workflows** in production environments * Design end-to-end solutions integrating APIs, enterprise systems, and data platforms * Partner directly with customers to translate business problems into scalable AI solutions * Own delivery from **prototype → production → iteration** * Optimize systems for performance, cost, and reliability * Contribute reusable patterns and influence product through real-world feedback **What We’re Looking For** * **5–8+ years** of software engineering experience (including applied or customer-facing work) * Strong coding skills in **Python and/or TypeScript** * Hands-on experience with **LLMs, prompt engineering, and production AI systems** * Experience building and deploying **complex, integrated systems** * Ability to operate in ambiguity and move quickly from idea to production * Strong communication skills with both engineers and business stakeholders **Strong Preference** * **PhD or Master’s in Computer Science (or related field)** * Experience with **agent frameworks, orchestration systems, or distributed systems** * Familiarity with LLM providers (OpenAI, Anthropic, Gemini, etc.) * Background in **applied AI, machine learning, or automation platforms** * Experience in **startup, consulting, or forward-deployed environments** **Why This Role** * **Build real AI systems in production** — not just prototypes * **Work directly with customers** solving high-value, complex problems * **Operate at the frontier of agentic AI + enterprise automation** * **Influence product direction** through hands-on experience * See your work drive **millions in business impact** **Additional Details** * Travel: \~20–30% to customer sites * Location: Bellevue preferred; exceptional remote candidates considered #LI-MH1 Maybe you don’t tick all the boxes above—but still think you’d be great for the job? Go ahead, apply anyway. Please. Because we know that experience comes in all shapes and sizes—and passion can’t be learned. Many of our roles allow for flexibility in when and where work gets done. Depending on the needs of the business and the role, the number of hybrid, office-based, and remote workers will vary from team to team. Applications are assessed on a rolling basis and there is no fixed deadline for this requisition. The application window may change depending on the volume of applications received or may close immediately if a qualified candidate is selected. We value a range of diverse backgrounds, experiences and ideas. We pride ourselves on our diversity and inclusive workplace that provides equal opportunities to all persons regardless of age, race, color, religion, sex, sexual orientation, gender identity, and expression, national origin, disability, neurodiversity, military and/or veteran status, or any other protected classes. Additionally, UiPath provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review these and other legal disclosures, visit our [privacy policy](https://www.uipath.com/legal/trust-and-security/privacy-policy).