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Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing. The Opportunity at Altana The Implementation team is the tip of the spear in getting Altana's platform into production inside our customers' businesses. We own the path from signed contract to realized value: standing up integrations, wiring Altana into the customer's existing business processes, and making sure the insight we deliver actually changes decisions on the customer's side. We are a delivery organization with a technical core. We work directly with customer stakeholders — from trade compliance analysts to enterprise IT — and we work just as closely with Altana's engineering, data science, and product teams to translate what we learn in the field into what gets built next. You Will Design and deploy agentic AI systems Design, build, and deploy agentic AI workflows — multi-step agents, tool and function calling, and automations — that power the customer's business processes and act on real customer data Ground agents in customer context: connect them to the right data sources, APIs, and systems of record, and define the tools, permissions, and guardrails they operate within Write and refine the prompts, system instructions, and evaluation criteria that make an agent reliable enough to trust in production Build the orchestration and human-in-the-loop checkpoints that keep agentic workflows safe, auditable, and correctable in a customer's environment Monitor, evaluate, and iterate on deployed processes — tracking accuracy, cost, and latency, and tuning them as the customer's data and needs evolve Own technology implementation and delivery Lead customer implementations end to end: scoping, configuration, integration, validation, go-live, and handoff to steady-state support Configure and deploy Altana's platform capabilities against real customer data and real customer

Who We Are At Justworks, you’ll enjoy a welcoming and casual environment, great benefits, wellness program offerings, company retreats, and the ability to interact with and learn from leaders in the startup community. We work hard and care about our most prized asset - our people. We’re helping businesses get off the ground by enabling them to focus on running their business. We solve HR issues. We’re data-driven and never stop iterating. If you’d like to work in a supportive, entrepreneurial environment, are interested in building something meaningful and having fun while doing it, we’d love to hear from you. We're united by shared goals and shared motivations at Justworks. These are best summed up in our company values, which are reflected in our product and in our team. Our Values If this sounds like you, you’ll fit right in. Who You Are Justworks is seeking a seasoned and strategic Senior People Business Partner with a strong record of developing and implementing people strategies and initiatives that meaningfully contribute to business results. As a Senior People Business Partner, you will be a trusted partner to your client group organizations, enabling leaders to build high-performing teams, and fostering an environment where Justworkers (employees) can grow, thrive and feel seen. You are a true HR guru. There is no problem too big or too small that you cannot tackle using your extensive knowledge and good judgement, making you an essential partner to the business and member of the People team. You skillfully balance the needs of the business with the experience of Justworkers, keeping our ambitious goals of helping small businesses grow with confidence top of mind. You’re curious and inquisitive, recognizing the need to gain relevant context and partner with the appropriate stakeholders to propose informed solutions to the business. If you thrive in fast-paced, matrixed environments and are energized by solving complex talent challenges at

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. What You'll Do Architect and implement scalable multi-agent systems: A2A collaboration, memory, reasoning, tool use, workflow orchestration, observability. Build agentic workflows on the Claude ecosystem: Claude Code–style engineering, MCP tool access, and AWS AgentCore runtime patterns. Design and optimize Vector RAG & GraphRAG: retrieval, semantic search, grounding, citation, graph traversal, and context engineering. Deliver technology-agnostic hybrid architecture: across AWS, GCP, Kubernetes, and on-prem/distributed data platforms. Partner across engineering, manufacturing, product, validation, and data teams; lead PoCs, mentor, and set standards. What You Bring (Required) Bachelor's or equivalent experience in CS, AI, Data Science, or a related field; 8+ years in software/AI-ML, enterprise, platform, or knowledge engineering. Validated delivery of enterprise-scale Agentic AI, Generative AI, and RAG/GraphRAG solutions. Hands-on Python plus agentic framewo

About the Team Agentic Foundations, part of New Verticals ML, builds the core AI/ML intelligence that powers high-quality, scalable agents at DoorDash, and proves it through flagship agent experiences such as the Ask grocery assistant. We operate as a closed loop: new models, evals, and representations make our agents better, and real-world agent usage surfaces the gaps that drive our next foundations work. About the Role We’re looking for a Senior Machine Learning Engineer to join Agentic Foundations with a primary focus on Vertical Agent Development. You will own the continuous improvement of our flagship agents, starting with the Ask Assistant, using an eval-driven loop to make them faster, more cost-efficient, and more reliable for millions of customers. You will also help us bring this approach to new agentic experiences for Merchants and Dashers, turning promising ideas into production-ready agents. This is a chance to work at the intersection of LLMs, agents, post-training, and evals on problems that ship. You will partner closely with engineers working on agentic memory, agent-compatible product representations, and post-training of small language models (SLMs), so that what we learn from production agents feeds directly back into our foundations, and what we build there makes our agents better. You will report into the engineering lead on our New Verticals AI/ML team. We expect this role to be hybrid with some time in-office and some time remote. You’re excited about this opportunity because you will… Raise the quality of our Consumer agents: build and refine our eval harness-optimization loop to pinpoint failure modes, then iterate on prompts, tools, skills, and context, and measure the impact on real customer tasks. Find the best balance of quality, latency, and cost: run rigorous experiments, including fine-tuning open-weights models and deploying small language models (SLMs) where they can replace or augment larger LLMs. Launch new agents: take ag

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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse, using open formats like Apache Iceberg, at dramatically lower cost. A dynamic Context Graph and chat-based AI SRE provide rich context and automated workflows so teams can move from detection to root cause of production issue and resolution 10x faster. Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world’s leading data platforms. The Team: We are hiring a Software Engineer, Enterprise for our Engineering team at Observe by Snowflake. As part of the Enterprise Engineering team at Observe by Snowflake, you’ll build and scale core features, APIs, and business logic powering a high-performance observability platform. You’ll develop reliable, production-grade systems designed to handle massive volumes of telemetry for enterprise customers. Working at the intersection

InMobi (Corporate) InMobi Group is a global technology company shaping the future of agentic commerce and advertising. Through its ecosystem of businesses — including InMobi Advertising and flagship consumer platform Glance — InMobi leverages data, machine learning, and generative AI to help brands reach audiences more precisely and consumers discover products more intuitively. Glance, which is pioneering new models of agentic commerce, is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd. InMobi Advertising InMobi Advertising, part of global technology company InMobi, is an agentic advertising platform helping brands and merchants achieve their business outcomes. Through its proprietary intelligence, AI-led solutions, and vast consumer reach — including flagship consumer platform Glance — InMobi Advertising delivers the omnichannel performance defining what's next in advertising and commerce. Glance is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd. To learn more, visit advertising.inmobi.com. Glance Glance is an intelligent shopping agent, redefining the commerce experience. Powered by proprietary agentic intelligence and generative AI, Glance delivers a hyper-personalized consumer experience across mobile and TV — shaping the new era of shopping. Glance is operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of global technology leader InMobi, and is backed by Mithril Capital, Google and Jio Platforms. To learn more, visit glance.com. InMobi Advertising is a global technology leader helping marketers win the moments that matter. Our advertising platform reaches over 2 billion people across 150+ countries and turns real-time context into business outcomes, delivering results grounded in privacy-first principles. Trusted by 30,000+ brands and leading publishers, InMobi is where intelligence, creativity, and accountability converge. By combining lock screens,

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the Role The Developer Infrastructure team builds the systems Sentry engineers use to develop, test, and ship software. We own local and cloud development environments, CI/CD across our open-source and private codebases, tooling for creating new services, and SDK and library publishing. Our goal is to help engineers spend more time building for customers and less time troubleshooting their development tools. You’ll work on problems such as shortening CI feedback cycles, improving deployment reliability, detecting flaky tests, and making development environments easier to use and maintain. As AI coding agents become part of engineering workflows, you’ll also help our environments, CI, and deployment systems support them with the context and access they need. You’ll own projects from design through rollout and ongoing operation, working directly with engineers across Sentry to understand their needs and measure whether your changes improve their work. This role is based in San Francisco, with three days per week in the office to work closely with Platform and Product Engineering teams. What You’ll Do Build and maintain tooling for local and cloud development environments. Improve the speed and reliability of CI and deployment pipelines as our codebases and infrastructure grow. Develop supported, reusable workflows for creating services and libraries. Improve SDK and library publishing tools and release processes. Build metrics, dashboards, and flaky test detection to help teams identify and resolve development and deployment problems. Give engineers and AI coding agents the context they need to work within Sentry’s syste

About Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. There is no MSSP and no tier-1 queue here. Detection & Response engineers own their detections end to end: you write them, you tune them, and your team is paged when they fire. The security team is spread across the globe with a follow-the-sun pager rotation so nobody is paged at 3am local. The adversaries are real. The business is growing fast and the threat surface is growing with it. Defining the necessary telemetry is part of the job. What You'll Do Detection engineering Build and tune detections across endpoint, identity, SaaS, and cloud , treating them as software: version-controlled, peer-reviewed, and shipped through the same CI/CD practices the rest of engineering uses. Track detection quality as measured quantities : coverage against MITRE ATT&CK, precision, time-to-detect. We don’t build-and-forget here. Response & automation Own EMEA-hours incident response: triage, contain, remediate, and write the retrospective that turns the incident into a systemic fix. Build automation that removes toil from investigations, and partner closely with the US-based team so context carries across time zones instead of getting lost at handoff. Telemetry &

About the Team OpenAI’s Physical Engineering work explores how frontier AI can help people design, simulate, and build better physical products. We work directly with customers to identify high-value engineering applications that shorten development cycles, improve product performance, and create measurable business value. About the Role We are hiring a Physical Engineering Business Lead to bring firsthand product engineering experience into our customer work. You’ll combine deep familiarity with CAD, simulation, or related engineering tools with the ability to lead customer discovery, explain complex ideas clearly, and turn promising use cases into high-impact projects. This is a hands-on, customer-facing role. You’ll work closely with customer engineering teams, senior leaders, forward-deployed engineers (FDEs), and account teams from early discovery through delivery. You’ll help frame valuable design and simulation problems, guide projects with practical engineering judgment, and support adoption and measurable outcomes. You’ll also turn what we learn from customers into product feedback, reusable delivery methods, and recommendations for our go-to-market and partnership strategies. As the work grows, this role may evolve into broader practice leadership. Key Responsibilities Lead discovery and workshops with customer engineering teams and senior leaders to identify high-value design and simulation use cases Develop promising use cases into significant projects with FDE and account teams, forming clear hypotheses about value, feasibility, engineering constraints, and adoption Work alongside FDEs and customer teams through delivery, bringing practical engineering context, surfacing risks early, and helping projects achieve measurable outcomes Explain how AI can improve physical-product engineering, grounded in real experience with CAD, simulation, engineering workflows, and design tradeoffs Build customer confidence through clear technical storytelling, compelling

SIXGEN’s mission is to deliver agile, mission-ready cybersecurity solutions that empower government and critical infrastructure organizations to stay ahead of advanced cyber threats. We combine innovation, deep expertise, and cutting-edge capabilities to uncover vulnerabilities, protect vital systems, and ensure operational superiority in an ever-evolving digital landscape. POSITION OVERVIEW Position: AI/ML Engineer Job Type: Full Time Location: Columbia, MD Clearance Requirement: TS/SCI, CI Poly Salary : Senior $215, SME $240K WHAT YOU’LL DO SIXGEN is actively seeking candidates to be part of a team that supports the United States Cyber Command (USCC). Our team is standing up USCYBERCOM’s AI Enterprise capability — the central hub that mission teams turn to when they want to move an AI solution from prototype to a secure, governed, enterprise-scale service. As a AI/ML Engineer on this team, you will design and integrate the models, agents, and AI workflows that run on that platform, with significant, visible impact on the mission of the USCC. What You'll Be Doing: Provide embedded operations support, capability integration, and rapid prototyping for AI/ML-enabled tools in support of our customer. Design and integrate LLM/agent orchestration workflows using agentic frameworks such as LangGraph, Agno, and the NVIDIA NeMo Agent Toolkit. Tune model gateway routing logic to select, evaluate, and optimize across multiple frontier and open-weight models for cost, performance, and mission fit. Develop and integrate RAG pipelines, vector databases, and memory services to give agents access to mission knowledge and context. Implement MCP (Model Context Protocol)-based tool-broker integrations so agents can safely and securely access enterprise tools and data. Evaluate, benchmark, and tune models and agent behaviors; build automated evaluation pipelines to track quality, safety, and performance over time. Partner with data scientists and mission analysts to

Who We Are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About The Team The Solutions Architecture (SA) organization helps Stripe's most strategic customers design and validate technical solutions that drive their business forward. Within SA, our team builds the tools, workflows, and custom technical assets that make the broader SA org more effective—turning individual ingenuity into org-wide capability. We are looking for AI Engineers who are energized by working close to the business and the users we serve. You'll operate as an embedded, high-context engineer focused on the highest-leverage opportunities across the SA org—building production-quality tooling, supporting our most strategic engagements, and shipping automation that meaningfully improves how Solutions Architects work every day. What You'll Do As an AI Engineer, you'll be embedded directly with the Solutions Architecture team—building alongside them, deeply understanding their workflows, and shipping tools and automation that permanently change how they operate. Your measure of success is SA productivity: the engagements you've accelerated, the workflows you've transformed, and the tools you've built that the org adopts as default. You'll ship code daily. You'll discover where SAs lose time and build high-impact solutions. You'll take what works for one person and scale it to work for the org. And when our most strategic customer engagements need custom technical assets, you'll build those too. This is a role for someone who wants to work at the in

About Wolt At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we’re building the delivery of (almost) everything and you’ll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe. Working at Wolt isn’t always easy, but it’s definitely exciting. Here you’ll learn more, build more, and ship more than in most other companies. You’ll be challenged a lot, but also have a lot of fun on the way. So, if you’re a self-starter with drive and entrepreneurial spirit, this could be the ride of your life. About the Team The Platform Hiring Team (PHT) is building a centralized, technology-enabled hiring engine for repeatable, high-volume roles across supported DoorDash, Deliveroo and Wolt businesses. You'll join Platform Hiring Operations, PHT's business-facing team. This team owns demand, market context, and pipeline health: translating business needs into hiring plans, keeping stakeholders ahead of risk, and clearing blockers before they reach the execution team. About the Role You'll own business readiness, attraction, and pipeline health for Courier hiring across the business, a new area for Platform Hiring. You'll translate business needs into hiring plans, validate demand against strategy and cost, coordinate Marketing and sourcing partners, activate roles when requirements are complete, and monitor progress against hiring dates. As the senior business-facing partner for Courier, you'll advise business leaders on hiring strategy, market conditions, timing, location, quality, and delivery trade-offs using funnel and talent-market evidence. When pipeline volume declines, you'll coordinate targeted sourcing interventions and ensure the execution team has sufficient pipeline. You'll proactively coordinate blockers across onboarding, background checks, traini

About Appier Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of “Making AI Easy by Making Software Intelligent,” Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com. About the Role We are looking for a Machine Learning Scientist (Modeling & Evaluation) to join the Enterprise Solution Science Team and help enterprises turn AI into real ROI. In this role, you will be responsible for end-to-end development, from problem definition to driving models and solutions into production. What You'll Work On Design, develop, and deploy optimization solutions built on ML models and evaluation, to improve efficiency and quality. Work with PMs and engineers to turn product goals and customer needs into clear problems and priorities, and integrate validated methods into the product. Build reliable evaluation methods for LLM output to measure the quality and impact of solutions, and decide if the results apply to real-world conditions. Form your own hypotheses, then design A/B tests that use real traffic to validate them. Follow the latest research and industry solutions, evaluate them in our own context, and propose new approaches. Decide what to build in-house and what to adopt. Monitor solutions after launch, and proactively communicate risks, trade-offs, and progress. (Optional) Mentor junior scientists and interns, if the need arises. What We're Looking For (Minimum Qualifications) Master's or PhD degree in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or related fields At least 2 years of experience in machine lea

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role Elastic Observability is building a system that monitors production environments the way an expert SRE would: it learns what normal looks like across logs, metrics, and traces, generates its own detection queries, identifies when something meaningful changes, and launches autonomous investigations — without waiting for a human to notice first. The goal is to close the gap between the alert that fires and the answer that matters, at a scale no on-call rotation can match. You will work on the Kibana UI, where Autonomous investigations meet the engineers who rely on them, making agent reasoning legible enough that an SRE can trust it, challenge it, and act on it. You will also work on the context and detection pipelines that turn raw telemetry into structured signals, the analysis that separates noise from events worth investigating, and the multi-agent system that digs into root causes autonomously and drives remediation. What You Will Be Doing You will work across our AI SRE solution. Over time, that will include the following: User-facing surfaces: Build the Kibana interfaces where signals, investigations, and findings reach users: the views an SRE uses to follow an investigation, inspect the evidence behind a conclusion, and drive the remediation that follows. This is most of the work today, though investigations increasingly ne

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role Elastic Observability is building a system that monitors production environments the way an expert SRE would: it learns what normal looks like across logs, metrics, and traces, generates its own detection queries, identifies when something meaningful changes, and launches autonomous investigations — without waiting for a human to notice first. The goal is to close the gap between the alert that fires and the answer that matters, at a scale no on-call rotation can match. You will work on the Kibana UI, where Autonomous investigations meet the engineers who rely on them, making agent reasoning legible enough that an SRE can trust it, challenge it, and act on it. You will also work on the context and detection pipelines that turn raw telemetry into structured signals, the analysis that separates noise from events worth investigating, and the multi-agent system that digs into root causes autonomously and drives remediation. What You Will Be Doing You will work across our AI SRE solution. Over time, that will include the following: User-facing surfaces: Build the Kibana interfaces where signals, investigations, and findings reach users: the views an SRE uses to follow an investigation, inspect the evidence behind a conclusion, and drive the remediation that follows. This is most of the work today, though investigations increasingly ne