As a Mobile Engineer supporting RoadieXD™, Roadie’s cross-dock solution, you’ll help build and maintain our warehousing mobile platform. You’ll collaborate with cross-functional teams to deliver scalable, high-quality features that support warehouse operations and improve the user experience.

What You’ll Do

• Contribute to the development of our warehousing mobile platform (e.g., order management, barcode scanning, RFID label printing, shipment tracking)
• Write clean, maintainable, and well-tested code
• Support ongoing improvements to core app functionality and assist with prototyping new features
• Help integrate new scanning and printing devices into the mobile platform
• Contribute to maintaining mobile repositories and supporting CI/CD workflows
• Collaborate with engineering, product, operations, and design to deliver solutions
• Partner with UX/UI designers to implement intuitive, user-friendly interfaces
• Apply best practices to improve app performance, reliability, and maintainability
• Occasionally travel to warehouse locations to better understand user needs and workflows

Technology We’re Using

• Mobile: Flutter/Dart, Android, Swift
• Backend & Infra: Postgres, Redis, Kafka, Firebase, GraphQL
• Cloud & DevOps: AWS, Docker, Kubernetes
• Tools: Git, GitHub, CircleCI

What You Bring

• 3+ years of software development experience
• 2+ years of experience with Flutter/Dart
• Experience building and shipping mobile applications
• Familiarity with integrating APIs and working with backend systems
• Basic understanding of mobile architecture and UI/UX principles
• Exposure to native mobile development (Android or iOS) is a plus
• Strong problem-solving skills and attention to detail
• Ability to collaborate effectively and communicate clearly
• Willingness to learn and grow in a fast-paced environment

Why Roadie? 

• Competitive compensation packages 
• 100% covered health insurance premiums for yourself
• 401k with company match
• Tuition and student loan repayment assistance (that’s right - Roadie will contribute directly to your existing student loans!) 
• Flexible work schedule with unlimited PTO 
• Monthly 3-day weekends
• Monthly WFH stipend 
• Paid sabbatical leave- tenured team members are given time to rest, relax, and explore
• The technology you need to get the job done

WE’RE HIRING! If you love data and are looking for unlimited growth opportunities, we want to talk with you about joining Further.

Further is a data, cloud, and AI company whose focus is helping companies turn raw data into the right decisions. We have an award winning culture of extraordinary people. Our purpose is to enable people to thrive so that businesses can thrive. We believe that the work you do should matter - it should be meaningful to you professionally and personally, and it should have a positive impact on both you and our clients.  If this sounds exciting to you, let’s chat!

SENIOR AI ENGINEER

We are hiring a Senior AI Engineer to lead the development of our cloud-based (Google Cloud), commercial AI products. You will bridge the gap between experimental data science prototypes and production-grade software. You will architect the robust systems and LLMOps workflows necessary to transform AI models into reliable, enterprise-ready applications. By designing stable backend architectures and seamless integration layers, you will ensure our AI solutions are not just functional, but ethical, efficient, and high-value products that meet the rigorous demands of our commercial clients.

What experience should you have:

• 6+ years of software engineering experience with at least 3 years dedicated to AI/ML application development.
• Expert proficiency in Python AI application development and modern API architecture (REST, GraphQL, gRPC) using enterprise standards like static type checking and data validation.
• Deep experience building production applications with LLM frameworks such as LangChain, LangGraph or LlamaIndex.
• Hands-on expertise with vector databases (Pinecone, Weaviate, PostgreSQL) and search algorithms.
• Strong understanding of LLMOps principles, including model registry, versioning, and serving infrastructure specifically in Google Cloud.
• Experience in Typescript development for prototyping and integrations
• Proficiency with git workflows and understanding of standard application development processes

Preferred Qualifications

• Knowledge of advanced prompt engineering and fine-tuning techniques (LoRA, PEFT).
• Experience optimizing inference costs and latency for large-scale deployments.
• Previous experience in a client-facing consulting role, managing diverse stakeholders and navigating complex organizational structures.
• Any Google Cloud Professional Certification

What you’ll be doing in this role:

• Lead the implementation of rigorous evaluation frameworks to monitor model performance, drift, and cost in real-time.
• Architect and develop high-performance backend services and APIs using Python (FastAPI) to serve large language models at scale.
• Design advanced Retrieval-Augmented Generation (RAG) systems, selecting and managing vector databases and optimizing embedding strategies for accuracy and speed.
• Establish comprehensive model observability and guardrail systems to monitor real-time performance, detect distribution drift, and implement automated safety filters that mitigate hallucinations, bias, and toxic outputs in production environments.
• Build robust integration layers that connect AI agents securely to external enterprise systems, CRMs, and legacy databases.
• Conduct code reviews, provide technical guidance, and foster a culture of continuous learning and innovation within the engineering team.
• Collaborate with infrastructure teams to define deployment strategies, ensuring solutions scale dynamically under load.
• Define the end-to-end architecture for AI products on cloud platforms (preferably Google Cloud Platform), ensuring high availability, security, and cost-effectiveness.

What you’ll need to accomplish in your first year:

• Develop reusable internal libraries and architectural patterns and standards to accelerate the delivery of AI solutions across multiple client engagements.
• Mentor engineers on best practices for building deterministic software around probabilistic AI models.

Our total rewards program is designed for your protection, peace of mind, and overall well-being. In addition to our outstanding basics, we offer a net-zero cost medical option, company contributions to your HSA, fertility support, fully-paid parental leave, a monthly stipend for your lifestyle spending account, and much more.

Apply today or check out all our opportunities!

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#LI-Hybrid

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AI Software Engineer – Cloud AI Platforms

At NICE, we are not just building software—we are transforming how cloud operations are run using AI. We are building intelligent platforms that can understand system behavior, make decisions, and automate real-world operational workflows at scale. If you’re excited about applying AI beyond chatbots into real production systems, this is an opportunity to work on meaningful, high-impact problems.

What’s the role all about?

As an AI Software Engineer, you will be part of a team building AI-powered operational platforms that integrate across monitoring systems, CI/CD pipelines, ticketing tools, and cloud infrastructure. You will work on designing and implementing intelligent workflows, integrating AI models, and building scalable systems that automate complex operational tasks.

This is a highly hands-on role focused on building, integrating, and scaling AI-driven solutions in production environments.

How will you make an impact?

• Build and scale AI-driven workflows and automation systems
• Develop integrations with systems like monitoring platforms, ticketing tools (ServiceNow, Jira, OpsGenie), CI/CD pipelines, and cloud services
• Design and implement APIs, tools, and data pipelines that power AI-driven decision-making
• Work on LLM integrations, prompt engineering, and orchestration layers — streaming responses, function calling, tool use, RAG pipelines, agentic orchestration
• Build and maintain full-stack AI applications using TypeScript, React, and Next.js — from user dashboards and personalized experiences to real-time analytics and interactive tools
• Translate real-world operational problems into automated, intelligent solutions
• Collaborate with Product, SRE, and Infrastructure teams to deliver end-to-end capabilities
• Improve system performance, reliability, and observability
• Build evaluation and observability systems — measure model capabilities, monitor output quality, and create dashboards that keep the product improvable
• Create reusable platforms and tools that accelerate development — component libraries, shared abstractions, internal tooling that multiplies team productivity

Key Responsibilities

• Design and develop scalable backend systems for AI-powered platforms
• Build and maintain AI integrations, workflows, and automation pipelines
• Implement REST APIs, microservices, and event-driven architectures
• Design and implement database schemas and queries for complex domains — tracking, engagement, reporting
• Work with both structured and unstructured data for AI use cases
• Contribute to CI/CD pipelines, testing, and deployment automation
• Troubleshoot and optimize production systems
• Collaborate with cross-functional teams to deliver high-quality solutions
• Contribute to reusable frameworks and engineering best practices
• Prototype fast — move from concept to working demo in days, ship incrementally

What we’re looking for

• 5+ years of software engineering experience, strong focus on full-stack web development
• Expert in TypeScript and React — performance optimization, modern patterns (hooks, context, suspense), component architecture
• Production experience with Next.js — App Router, Server Components, API routes, SSR/SSG, edge deployment
• Hands-on experience with LLMs — prompt engineering, streaming APIs, function calling, tool-use, chaining and orchestration patterns
• Experience with Vercel AI SDK — unified LLM provider interface, streaming, structured output, tool calling across OpenAI/Anthropic/Google/xAI
• Model Context Protocol (MCP) — building or consuming MCP servers for extensible AI tool use
• Strong backend fundamentals — Node.js or Python, REST/GraphQL APIs, relational databases, Redis, auth
• Solid database design — PostgreSQL, Drizzle ORM, schema modeling for complex domains, query optimization, migrations
• Experience building scalable, distributed systems in cloud environments (AWS / Azure)
• Working knowledge of CI/CD, Docker, Kubernetes
• Familiarity with Tailwind CSS, Radix UI and modern component-driven UI development
• High agency — you operate independently in ambiguous environments, take ownership of problems, and drive them to completion
• Strong problem-solving and analytical skills
• Ability to work in a fast-paced, evolving environment
• Communicate effectively with both technical and non-technical stakeholders

Nice to have

• Experience building agentic coding tools, AI agent frameworks, or developer-facing SDKs/APIs (Claude Agent SDK, OpenAI Agents SDK)
• Experience with Vercel ecosystem — Next.js, AI SDK providers, Turbopack
• Background in evaluation frameworks — measuring model capabilities, collecting human feedback at scale, A/B testing outputs
• Experience with sandboxed execution environments for safely running AI-generated code
• Built research tools, experimentation platforms, or scientific software
• Proficiency with Python — FastAPI/Django, data pipelines, ML tooling
• Knowledge of observability tools (Grafana, Prometheus, Sentry, etc.)
• Experience building automation or internal platforms
• Familiarity with real-time features — WebSockets, streaming UX, collaborative interfaces
• Knowledge of advanced web technologies — WebGL, WebAssembly, web workers, PWAs
• Experience with alternate JS runtimes — Bun, Deno
• Built open-source tools or platforms with active user communities
• Strong quantitative foundation (math, physics, or related fields)

Representative Projects

Things you might build in this role:

• Interfaces for collecting and managing human feedback on model outputs at scale
• Experiment orchestration platforms — launch, monitor, and analyze complex AI research runs
• Visualization tools that help understand model behavior and identify failure modes
• Reusable components and frameworks that enable rapid development of new AI applications
• Sandboxed execution environments for safely running AI-generated code
• AI-powered personalization engines — tutoring, content generation, adaptive features
• Workflow builders that let non-engineers orchestrate AI capabilities visually
• Enterprise integrations — ServiceNow, Salesforce, Confluence, Jira