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Your wellbeing, our mission. Join a company shaping a healthier world. GET TO KNOW US At Wellhub we're revolutionizing workplace wellness. Our platform connects employees worldwide to the best partners for fitness, mindfulness, therapy, nutrition, and sleep—all in one simple subscription. Headquartered in NYC with team members in Europe, North America and South America, we’re on a mission to make every company a wellness company. We believe work should be fulfilling, inspiring, and balanced. Here, you’ll find a team that values wellbeing, collaboration, and different perspectives, where passion and creativity push boundaries to create real impact. Your contributions will help shape a healthier, more balanced world for you and millions of people globally. Join us in redefining the future of wellbeing! THE OPPORTUNITY We are hiring a Senior AI Platform Engineer to our Product Development team in Brazil ! This is a Remote – Brazil position, meaning you can work from anywhere within the country. Please note that this role is only open to candidates in Brazil. Join the ML Development Lifecycle team within our Product Development (PD) organisation, where we are redefining how a global tech company leverages intelligence. We build the foundations that allow hundreds of engineers and data scientists to develop and deploy AI at scale. You will own the evolution of our cloud-native ecosystem , creating a seamless and high-performance environment for the next generation of AI-driven products. If you are a software-minded engineer who thrives at the intersection of scalable Infrastructure and ML/AI orchestration, this is your chance to build a world-class platform that serves millions of users worldwide. YOUR IMPACT Scale the Ecosystem: Evolve and maintain our Kubeflow, Feast and Spark-on-Kubernetes infrastructure, ensuring it can handle the increasing complexity of both traditional ML and the new wave of AI. Build for Autonomy:

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Our Senior Applied AI Engineer builds and operate production-grade AI systems that extract meaning from large-scale unstructured document collections, enabling enterprise data discovery classification, and governance. This role owns the full lifecycle of graph intelligence solutions — from problem definition and data modelling, to building and enriching knowledge graphs, and deploying ML- and LLM-assisted analytics in production. The focus is on semantic and contextual analysis of unstructured data to uncover relationships, patterns, and insights that support AI safety, security, and compliance requirements. WHAT YOU'LL DO Design, build, and deploy graph-based AI solutions, combining knowledge graphs , LLMs, and ML models applied to large-scale unstructured data Define and own data pipelines that extract, transform, and enrich entity relationships into production-grade knowledge graphs Integrate LLMs and ML models into text processing pipelines for classification, embedding generation, document similarity, and semantic analysis Design, deploy, and operate graph and vector databases to support retrieval, reasoning, and analytics Optimize models and inference pipelines for production constraints including latency, throughput, cost, and infrastructure Deploy, monitor, and iterate on ML systems in production environments ensuring reliability and continuous integration Drive architectural decisions and tech

Bloomreach is building the world’s premier agentic platform for personalization .We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the entire customer journey. We're taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses. We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey. We're designing the future of autonomous marketing , taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do. And we're building all of that on the intelligence of a single AI engine — Loomi — so that personalization isn't only autonomous…it's also consistent.From retail to financial services, hospitality to gaming, businesses use Bloomreach to drive higher growth and lasting loyalty. We power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora. You'd be joining the Artificial Intelligence team . We own the algorithmic core of the platform: Predictions, Contextual Personalization, contextual bandits, autosegmentation, and the agentic workflows behind Loomi. We work with behavioural data at terabyte scale, across 1,400+ customers, in production, every day. You'll work on cutting-edge technologies, impacting millions of users, and contributing to a product that truly makes a difference. Working in one of our Central European offices (Bratislava, Brno, Prague) or from home (Czechia, Slovakia) on a full-time basis , you´ll become a core part of the Engineering Team . The mission You turn a model that works in an experiment into a service that works for 1,400 customers. You own ML-powered features end to end — the API that configures them,

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

Role: Senior AI Engineer Location: Hyderabad, India (Hybrid) Department: Product Development About the Role GHX is building a cutting-edge LLM-powered document understanding platform focused on classification, structured data extraction, and intelligent orchestration at scale. This is a high-impact AI engineering role where you will own the full lifecycle—from problem framing to production deployment . Initially, you will focus on prompt engineering and evaluation systems , building the quality foundation for AI performance. Over time, the role expands into agent orchestration, system architecture, and migration of rule-based systems to LLM-driven pipelines . A strong foundation in software engineering (5+ years) is essential. This role demands engineering rigor across both traditional system design and AI system behavior . Core Responsibilities 1. Prompt Engineering Design prompts for diverse document classification and extraction tasks Treat prompts as formal specifications (precise, structured, and edge-case-aware) Develop few-shot, chain-of-thought, and structured output templates Manage prompt lifecycle: versioning, testing, and rollback 2. LLM Output Evaluation Create and maintain ground truth datasets Build automated evaluation pipelines (precision, recall, field-level accuracy) Identify and resolve conceptually incorrect outputs despite surface correctness 3. AI Agent Orchestration Design multi-agent workflows for document processing Implement tool-use patterns and integrate MCP servers Optimize orchestration for scale and efficiency 4. Software Engineering Develop production-grade APIs and backend services Apply Clean Architecture / DDD principles Write maintainable, testable Python code Contribute to CI/CD, deployment, and observability systems 5. Stakeholder Collaboration Act as a bridge between business stakeholders and AI systems Translate product requirements into technical architectures Communicate system behavior, limitations, and quality

Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world’s most important decisions. We’re looking for an AI Product Manager to own the Finance vertical within our Agents Data & Reinforcement Learning Environments team. In this role, you’ll own both the development of RL environments (the realistic, high-fidelity simulations of financial software and workflows that labs use to train and evaluate agents) and the “data as a product” strategy that powers them. You’ll understand where AI is being used in the Finance industry, decide what financial tasks are worth modeling, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside the Finance industry, and is able to pair that domain understanding with a sense for AI research and current agent capabilities in Finance workflows. You’ll translate that expertise into environments and datasets that teach AI agents to perform real financial work, and you’ll be the domain expert Scale’s most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You’ll Do Own the Finance AI roadmap & data strategy: Set product direction for the Finance agents training stack and the data strategy behind it. Establish a vision for where AI is continuing to transform the Finance industry (including investment banking, private equity, public markets, corporate finance, FP&A, etc), driving execution across engineering, operations, and go-to-market teams. Build partnerships with research teams at frontier labs: Work directly with researchers at leading AI labs to understand where their Finance agentic capabilities fall short and shape new product lines and competit

About the role: We are seeking a Senior Backend Engineer with deep backend engineering expertise and proficiency in one or more major programming languages (e.g., Python, Java, Go, Rust, or Kotlin), along with a strong understanding of AI models and agents. As a core member of our AI Engineering team, you will collaborate with data scientists, ML engineers, and product managers to build scalable, production-ready infrastructure and APIs that power intelligent systems. What you'll be doing: As a Senior Backend Engineer in the AI Engineering team, you will: Build and maintain reliable, scalable backend services to support AI agent execution and orchestration. Develop AI agent systems for complex operational workflows using LangChain, LangGraph, LiteLLM, and Langfuse. Orchestrate a hybrid model stack that includes OpenAI and Google Gemini alongside self-hosted and fine-tuned LLMs like Gemma and Llama. Build and maintain integrations with clinical systems (FHIR, EMR). Drive observability and reliability using OpenTelemetry, Datadog, and Langfuse. Design APIs (GraphQL, REST), background workers, and event-driven systems that interface with AI inference engines and agent runtimes. Collaborate with Data Science, ML, and engineering teams to deploy AI features and improve the performance, scalability, and reliability of backend systems. Participate in code reviews, knowledge sharing, and mentoring to elevate the team’s technical capabilities. What we're looking for: 6+ years of backend engineering experience, with strong proficiency in more than one major programming language (such as Python, Java, Go, Rust, or Kotlin). Solid understanding of AI systems architecture and experience working in environments involving AI agents, LLMs, or inference pipelines. Proven experience in building and scaling backend APIs, microservices, and background jobs. Strong experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Redis), including schema des

At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it's medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable. Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity. As a Senior AI Engineer, you'll join a 10-person team focused on data integrations (shippers and carriers moving in and out of the FourKites ecosystem) and our active AI agent workstreams — including a support automation agent handling 60-70% of customer tickets, a voice agent that calls carriers to gather and update information, and an end-to-end carrier onboarding agent (email + voice). You'll work on features end to end (~75-80% backend, ~20-25% frontend) using Python, Java/GoLang, agentic frameworks like LangGraph, React, Redis and PostgreSQL. You'll develop products that change the logistics landscape for some of the biggest corporations in the world, and work closely with our US team and customers to shape the future of the industry. What you’ll be doing: Design, build, and productionize AI agents/workflows (e.g., support automation, voice, and onboarding agents) using agentic frameworks such as LangGraph Develop, test, and maintain backend applications in Python and Java or GoLang Write clean, efficient, and well-documented code across the full SDLC — development, QA, and release Design and implement data models and database schemas Collaborate with the frontend team to integrate the backend with the user interface Perform code reviews and ensure code quality standards are met Troubleshoot and debug applications, including AI agent workflows in production Work with the DevOps team to deploy and manage applications in production (Kubernetes) Continuously learn and stay up to date with new technologies and industry trends, particularly in the AI/agentic space About the team: Our

Title: Senior AI QA Engineer Location: Bengaluru (Bangalore) Opportunity: As a Senior AI QA Engineer for our Precision Patient Care Pipeline , you will go beyond traditional functional testing. You will be responsible for building the framework that ensures our clinical insights are accurate, safe, and reliable. This role requires a unique blend of high-level software testing and data engineering to validate complex, non-deterministic medical outputs using a hybrid of automated grading methodologies . Key Responsibilities: Architect Multi-Layered Validation Frameworks: Design and implement structured testing strategies that combine deterministic checks, semantic similarity metrics, and model-based evaluations. Automated Model Grading: Develop systems to evaluate clinical pipeline outputs for faithfulness, safety, and hallucination detection using various automated scoring techniques (e.g., BERTScore, ROUGE, or custom heuristics). Vibe-Driven Development: Leverage agentic AI tools to rapidly prototype complex test harnesses, "red-team" clinical logic, and build internal validation utilities at high velocity. Data Pipeline Integrity: Execute integration and regression tests for data-heavy backend processes, ensuring medical data remains consistent from ingestion to insight generation. Collaborative Strategy: Work closely with Data Scientists and Product Managers to define "Ground Truth" datasets and clinical evaluation rubrics. Root Cause Analysis: Deep-dive into complex system failures to identify whether issues stem from code logic, data drift, or model behavior. Requirements: 6+ years of technical experience in Quality Assurance, with a strong focus on system architecture and backend data validation. Advanced Python Proficiency: Expert-level skills in Python for building custom test scripts and working within AI/ML ecosystems. AI/ML Validation Experience: Proven experience testing model outputs using diverse metrics (e.g., Semantic Similarity, NLP metrics, an

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role In an AI-native environment, the product shifts fast, new workflows emerge weekly, and customers and internal teams surface needs in real time. Someone has to meet those needs at the speed they arise. That's this role. As a lead learning experience designer, you'll own a fast-paced, high-volume learning design track focused on short, targeted, just-in-time courses — typically 15–45 minutes each, built in sprints of three weeks or less, shipping roughly 15+ courses per year. You'll build focused one-off courses that plug specific gaps: a new workflow, a role-specific skill, a tool that just shipped, an AI topic that can't wait for the next curriculum cycle. These courses are standalone, purpose-built, and often shorter-lived — responding to the moment. You'll work both proactively (scanning for emerging needs) and reactively (fielding requests from across the company and from customers). The pace is fast, the iteration cycles are tight, and the environment is dy

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Our Solution Engineering organization is seeking an AI Specialist who can provide hands-on expertise and support while working with technical decision makers and data scientists to design and architect AI solutions built on the Snowflake AI Data Cloud. This is a strategic role that works closely with cross-functional teams, including product, engineering, and the broader field organization to ensure successful execution and customer adoption of Snowflake’s AI & ML solutions. IN THIS ROLE YOU WILL GET TO: Be the technical expert in the room that positions Snowflake’s AI and ML features and value to technical stakeholders at Snowflake’s customers across the Americas. Partner with Snowflake account team teams and customer champions to scope and drive POCs to success and technical wins that prove the value of Snowflake’s capabilities, including executive readouts and business value cases. Collaborate with Snowflake’s product and engineering teams to influence Snowflake’s AI and ML roadmaps based on customer feedback. Publish content that helps the team and company scale beyond your individual efforts, like blog posts, presentations at conferences, or technical collateral like notebooks and demos. Influence, tailor and maintain Sales Engineering AI and ML selling assets, inc

Become a part of our caring community The Senior Full Stack Engineer Performs software engineering activities in all layers of the stack, from setting up the database to programming in the back-end and the appearance at the front-end. The Senior Full Stack Engineer work assignments involve moderately complex to complex issues where the analysis of situations or data requires an in-depth evaluation of variable factors. As Centerwell builds its AI engineering function from the ground up, we need a platform foundation strong enough to support everything that comes next. As Lead Full-Stack Engineer focused on platform and API engineering, you will design and build the service layer that connects AI capabilities, data systems, and product frontends—setting the standards for how services are built, secured, and operated across the team. You will work with meaningful architectural scope, making decisions that span API design, security patterns, and deployment practices. The platform you build will serve care teams and patients across hundreds of Centerwell clinics. If you want to build platforms that others build on—and do it in service of better primary care—this is the role for you. Key Responsibilities Platform and API Architecture: ** Design and lead development of core backend services, REST and GraphQL APIs, and service-to-service integrations that connect all layers of Centerwell's AI product stack. Security and Compliance by Design: ** Establish patterns for authentication, authorization, rate limiting, PHI access control, and audit logging. Ensure HIPAA compliance is embedded in platform design from day one—not bolted on after the fact. AI and LLM Integration Patterns: ** Define and implement reusable patterns for integrating AI capabilities into product

Become a part of our caring community Most AI engineering jobs are a thin wrapper around a model API. This role is different. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to the source document, and route ambiguous cases to human experts for review. Our users make decisions that impact real healthcare outcomes, so “good enough” is not good enough. Building AI systems that are accurate, reliable, auditable, and scalable is at the core of this role. As a Senior AI Applied Engineer, you will design, build, deploy, and operate production AI systems used at scale within one of the largest health insurers in the United States. You will own solutions end-to-end, from user experience and APIs to model orchestration, evaluation frameworks, infrastructure, and production operations. Why Join Us Build production AI systems where LLMs are in the critical path, not just demos or proofs of concept. Work on extraction, retrieval, agentic workflows, and human-review systems that process real healthcare data at scale. Own projects end-to-end across frontend, backend, AI orchestration, infrastructure, deployment, and operations. Solve challenging problems around accuracy, explainability, traceability, and reliability in regulated environments. Ship quickly in a small, high-impact team that embraces AI-assisted development and rigorous quality standards. Build systems that continuously improve through expert feedback, evaluations, and human-in-the-loop workflows. Key Responsibilities Design, develop, and deploy full-stack AI-powered application

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. What you’ll be doing: Use and develop AI-powered tools to make software testing smarter, faster, and more effective! Improve test case generation, defect detection, flaky test analysis, regression testing, and test coverage optimization. Work with product, engineering, and cross-functional teams to review requirements and define test strategies. Build test plans, design and execute test cases, and report quality status, risks, bugs, and results. Perform functional, performance, fault-injection, reliability, and regression testing for cloud-native systems. Automate test cases and contribute to scalable test frameworks. Manage the bug lifecycle, reproduce customer issues, and verify fixes. What we need to see: MS or PhD in Computer Science, Engineering, or a related field. 5+ years of QA, test automation, or software testing experience. Hands-on experience using AI tools to improve QA workflows. Strong QA fundamentals, test strategy, test planning, and failure analysis skills. Proficiency with Unix/Linux and shell or Python programming. Exp

We're Hiring Senior AI Engineer (Generative AI Azure) Remote Immediate Joiners Preferred Salary: Up to 12 LPA We are seeking an experienced Senior AI Engineer to design, develop, and deploy enterprise-grade Generative AI solutions on Microsoft Azure. The ideal candidate will have strong expertise in Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), Azure AI Services, and modern AI engineering practices. Technical Summary • AI & LLMs: Azure OpenAI, GPT-4.x, OpenAI, Prompt Engineering, Prompt Chaining, Function Calling, Structured Outputs, Tool Calling, JSON Schema, Model Evaluation, Guardrails, Fine-tuning Concepts • Agentic AI: Multi-step Reasoning, Planning, Memory Management, Tool Orchestration, Multi-Agent Systems, Human-in-the-Loop Workflows, Reflection, Context Management, AI Observability • Frameworks: Semantic Kernel, LangChain, LangGraph, AutoGen, Azure AI Agent Service • RAG & MCP: Retrieval-Augmented Generation, Vector Search, Semantic Search, Hybrid Search, Embeddings, Knowledge Grounding, Citation Generation, Document Ingestion, Chunking, MCP Architecture, MCP Servers & Clients • Azure Technologies: Azure AI Foundry, Azure AI Search, Azure AI Document Intelligence, Azure Machine Learning, Azure Functions, API Management, Logic Apps, App Service, Container Apps, AKS, Azure Storage, Data Lake Gen2, Azure Key Vault, Azure Entra ID, Azure Monitor, Application Insights, Event Grid, Service Bus • Programming & DevOps: Python, C#, REST APIs, FastAPI, ASP.NET Core, JSON, YAML, Git, Azure DevOps, Docker, Kubernetes • Data Platforms: SQL Server, Azure SQL, PostgreSQL, Cosmos DB, Snowflake, Microsoft Fabric, Azure Databricks, Delta Lake, Vector Databases (Azure AI Search, Pinecone, Weaviate, Milvus, Qdrant) • Security & Governance: Responsible AI, Prompt Injection Prevention, RBAC, Content Filtering, Data Privacy, GDPR, ISO 27001, Azure Key Vault, Audit Logging & Monitoring • Nice to Have: Microsoft Copilo