Agentic Ai Engineer Jobs

AI Fullstack Engineer Poland ABOUT US Capco is seeking experienced and motivated AI Engineers to help design, build, and deploy AI-enabled solutions for clients in the financial services industry. As part of this engagement, you will work on complex business, technology, and data challenges, applying modern AI engineering practices to create scalable, reliable, and production-ready solutions. We are seeking professionals combines strong software engineering skills with practical experience in large language models, machine learning, data platforms, and modern AI application development. You will collaborate with client stakeholders, product teams, data specialists, and engineers to turn business needs into AI capabilities that are explainable, maintainable, and aligned with enterprise standards. SCOPE OF SERVICES AI Solution Delivery Design, develop, test, and deploy AI-enabled applications and services. Build solutions using large language models, machine learning, retrieval-augmented generation, semantic search, and agentic AI patterns where appropriate. Translate client business problems into technical designs, implementation plans, and working software. Develop reusable AI components, APIs, prompts, workflows, and evaluation approaches. Ensure AI solutions are scalable, reliable, secure, and suitable for production use. Data, Knowledge, and Retrieval Engineering Work with structured and unstructured data sources to support AI-enabled discovery, reasoning, and decision support. Build or integrate search, retrieval, ranking, and knowledge management capabilities. Develop approaches that help AI systems understand business context, data assets, metadata, documentation, and other enterprise knowledge sources. Improve the quality, relevance, traceability, and explainability of AI-generated outputs. Collaborate with data engineering and platform teams to ensure AI solutions are well integrated with existing data ecosystems. Technical

We are seeking a highly analytical and technical professional to spearhead the evolution of our trading infrastructure. This hybrid role combines the fast-paced execution of a Trading Operations Specialist, the analytical rigor of a Risk Manager, and the technical capabilities of an AI-focused Developer. The successful candidate will not only manage daily operational workflows and risk monitoring but will also lead the digital transformation of these functions. You will leverage Large Language Models (LLMs), machine learning, and advanced scripting to automate legacy manual processes, improve predictive risk modeling, and build real-time performance visualization tools and analyses. Key Responsibilities: 1. Trading Operations and Performance Analysis with AI Manage the end-to-end lifecycle of trades across multi-asset classes. Develop agentic AI workflows using Python (ML) and MLOps tools to automate manual operations and reconciliations Perform daily P&L attribution and explain variance by decomposing market moves, Greeks, and new activity. Leverage AI/ML frameworks (e.g., OpenAI API, LangChain, or local LLMs) to build intelligent agents for anomaly detection in trade data and automated commentary generation for P&L reports. Ensure data integrity across trading systems, middle-office platforms, and downstream finance ledgers. Use AI tools to build reporting and analyses on trading performance and perform adhoc business analytics 2. Risk Monitoring & Control Intelligent Risk Management: Develop real-time, AI-driven risk models that use machine learning to predict market volatility and alert the desk to emerging cross-market risks. Develop and maintain sophisticated risk reporting dashboards for the desk. Requirements & Qualifications: Experience: 3+ years in front-office operations, quant

We are seeking a highly analytical and technical professional to spearhead the evolution of our trading infrastructure. This hybrid role combines the fast-paced execution of a Trading Operations Specialist, the analytical rigor of a Risk Manager, and the technical capabilities of an AI-focused Developer. The successful candidate will not only manage daily operational workflows and risk monitoring but will also lead the digital transformation of these functions. You will leverage Large Language Models (LLMs), machine learning, and advanced scripting to automate legacy manual processes, improve predictive risk modeling, and build real-time performance visualization tools and analyses. Key Responsibilities: 1. Trading Operations and Performance Analysis with AI Manage the end-to-end lifecycle of trades across multi-asset classes. Develop agentic AI workflows using Python (ML) and MLOps tools to automate manual operations and reconciliations Perform daily P&L attribution and explain variance by decomposing market moves, Greeks, and new activity. Leverage AI/ML frameworks (e.g., OpenAI API, LangChain, or local LLMs) to build intelligent agents for anomaly detection in trade data and automated commentary generation for P&L reports. Ensure data integrity across trading systems, middle-office platforms, and downstream finance ledgers. Use AI tools to build reporting and analyses on trading performance and perform adhoc business analytics 2. Risk Monitoring & Control Intelligent Risk Management: Develop real-time, AI-driven risk models that use machine learning to predict market volatility and alert the desk to emerging cross-market risks. Develop and maintain sophisticated risk reporting dashboards for the desk. Requirements & Qualifications: Experience: 3+ years i

We are seeking a highly analytical and technical professional to spearhead the evolution of our trading infrastructure. This hybrid role combines the fast-paced execution of a Trading Operations Specialist, the analytical rigor of a Risk Manager, and the technical capabilities of an AI-focused Developer. The successful candidate will not only manage daily operational workflows and risk monitoring but will also lead the digital transformation of these functions. You will leverage Large Language Models (LLMs), machine learning, and advanced scripting to automate legacy manual processes, improve predictive risk modeling, and build real-time performance visualization tools and analyses. Key Responsibilities: 1. Trading Operations and Performance Analysis with AI Manage the end-to-end lifecycle of trades across multi-asset classes. Develop agentic AI workflows using Python (ML) and MLOps tools to automate manual operations and reconciliations Perform daily P&L attribution and explain variance by decomposing market moves, Greeks, and new activity. Leverage AI/ML frameworks (e.g., OpenAI API, LangChain, or local LLMs) to build intelligent agents for anomaly detection in trade data and automated commentary generation for P&L reports. Ensure data integrity across trading systems, middle-office platforms, and downstream finance ledgers. Use AI tools to build reporting and analyses on trading performance and perform adhoc business analytics 2. Risk Monitoring & Control Intelligent Risk Management: Develop real-time, AI-driven risk models that use machine learning to predict market volatility and alert the desk to emerging cross-market risks. Develop and maintain sophisticated risk reporting dashboards for the desk. Requirements & Qualifications: Experience: 3+ years i

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Staff/Principal Full-Stack AI Engineer, IPAI, SMAI Job Summary Lead the Future of AI-Powered Manufacturing at Micron Micron is accelerating its transformation toward Autonomous Operations through Artificial Intelligence, advanced analytics, digital twins, robotics, and intelligent automation. As a Staff/Principal Full-Stack AI Engineer , you will be a technical leader driving the strategy, architecture, and delivery of next-generation AI products that power smarter manufacturing across Micron's global network of fabs and assembly/test sites. In this highly influential role, you will own AI solutions end-to-end—from data engineering, machine learning, and agentic AI systems to modern full-stack applications, digital twin platforms, robotics integration, and edge-to-cloud deployment. Working closely with data scientists, software engineers, robotics teams, and manufacturing leaders, you will transform innovative ideas into scalable, production-grade solutions that improve efficiency, increase automation, and enable intelligent decision-making at enterprise scale. This is a unique opportunity to shape the future of AI in semiconductor manufacturing and directly contribute to Micron's vision of autonomous, data-dri

About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . Your role As a Sr. AI Engineer: Systems, you’ll serve as an embedded senior back-end engineer on our Speech Team, owning the production systems that turn speech models and third-party capabilities into reliable, scalable experiences for Dialpad’s AI voice agents. You’ll work at the intersection of speech, ML infrastructure, and

Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: Drata's AI Platform team builds the production infrastructure that powers AI features across our compliance platform — from MCP servers that make Drata's data available to AI agents, to LLM workflow orchestration that automates SOC 2, TPRM, and policy analysis. You'll own the systems that sit between our AI models and our customers: tool definitions that agents actually understand,

Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: Drata is seeking a Senior Applied AI Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research. This is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with

Senior Software Engineer, Applied AI About Syllo Syllo is on a mission to transform litigation. Our product is a unified litigation platform that enables lawyers and paralegals to safely harness the power of language models and agentic AI throughout the litigation life cycle. Since going to market, we have gained a diverse group of enterprise customers, including some of the biggest law firms and corporations in the country, and we are quickly expanding. By reducing the expense of litigation industry-wide, we aim to improve access to high-quality representation and promote the alignment of legal outcomes with merit. About the Role We are seeking a skilled and fast-moving Applied AI Engineer to join our team. This role is focused on the practical application of AI, specifically leveraging Large Language Models (LLMs), to build robust, scalable, and impactful user-facing features. This is an engineering-centric role. You will be an expert at building and integrating production systems, not primarily a research scientist. Responsibilities Design and build high-performance, production-level AI-powered features and services, with a focus on reliability and scalability. Develop robust engineering solutions to mitigate the inherent unreliability of LLMs. This includes implementing effective guardrails, validation pipelines, error handling, caching, and failover/fallback mechanisms to ensure a high-quality user experience even when the model misbehaves. Design long-running batch processing that is idempotent, resumable, and resilient to individual item failures. Focus on optimizing latency, throughput, and cost efficiency for all AI-powered services. Serve as an engineering expert in integrating models and data feeds with existing business logic and APIs. Define and implement evaluation for AI feature output quality, not only system correctness. Implement rigorous testing strategies, including unit, integration, and performance testing, to ensure the robus

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As an Intermediate Backend Engineer (Python) in GitLab's Agent Foundations stage, you'll go beyond using AI tools. You'll help build the foundations for GitLab's agentic AI experiences: the platform that lets AI agents work across the whole software delivery lifecycle, not just write code. That covers the reusable building blocks agents and flows are made from as well as our core harness, Duo Developer. Most of your work will be backend engineering in Python, using libraries such as LangGraph to build secure, reliable and scalable features in our AI Gateway. You'll also work across the stack where needed.

Why Translucent Healthcare providers drive $2.5 trillion in medical expenditures annually — and operate on razor-thin 2–5% margins. Despite these stakes, the finance teams behind these organizations are buried in spreadsheets, manual data pulls, and disconnected systems, spending more time finding and cleaning data than actually using it to make decisions. Translucent is changing that. We're building the agentic AI platform designed exclusively for healthcare finance — giving every finance team, department, service line their own arsenal of AI Agents that run 24/7, understand their specific data, business logic, and workflows. Founded in 2024 and backed by GV, NEA, FPV, and Virtue, we've already been deployed by healthcare organizations managing over $5 billion in combined revenue. The product-market fit is real, the problem is massive, and we're just getting started. If you want to work at the intersection of AI and one of the most complex, consequential industries in the world — this is the place. About the role We're hiring a Forward Deployed Insights Engineer to join our team in New York. You will sit at the intersection of our customers' healthcare finance problems and the agentic AI and ML systems we build to solve them. Working on top of the unified data ontology our Analytics Engineers maintain and the agent infrastructure our AI Engineering team builds, you will stand up new agents and ML models for specific customer problems, configure the visualizations and presentation layer that make their outputs usable, and work directly with customers and end users to turn those capabilities into real, trusted decisions. This is a high-ownership, customer-facing role. You will partner closely with our product team to make sure the solutions you build for one customer become repeatable, platform-wide offerings. What you'll do Configure customer workspaces and build new AI agents and ML models on top of existing agent infrastructure and platform capabilities — our AI E

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As an Intermediate Backend Engineer in GitLab's Agent Foundations stage, you'll go beyond using AI tools. You'll help build the foundations for GitLab's agentic AI experiences: the platform that lets AI agents work across the whole software delivery lifecycle, not just write code. That covers how agents are created, shared and connected to tools inside and outside GitLab, how they run, and how their work shows up and can be observed across GitLab. In this role you'll work closely with engineers across the stage and other AI Engineering teams. This is a high-visibility area where GitLab's core platform mee

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Job Summary: Join the Product Engineering team to develop and deploy Artificial Intelligence (AI) and Machine Learning (ML) solutions that transform semiconductor manufacturing and engineering workflows. This role is responsible for building predictive analytics models, developing agentic AI solutions, enabling intelligent automation, and driving data-driven decision-making to improve yield, quality, cycle time, reliability, and cost efficiency. The successful candidate will leverage advanced machine learning techniques, large-scale semiconductor datasets, and AI technologies to solve complex engineering challenges. In addition, this role will mentor and enable Citizen Data Scientists (CDS) by providing technical guidance, training, and best practices in machine learning, analytics, and AI adoption. Strong technical expertise, innovation, collaboration, and communication skills are essential for success. Main Responsibilities: Machine Learning Development Develop, validate, and deploy machine learning models for yield prediction, test time optimization, reliability analysis, and manufacturing process improvement. Apply advanced analytics and machine learning techniques to large-scale structured and semiconductor manufactur

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. Job Summary – Member of Technical Staff - Agentic AI Architect, Smart Manufacturing AI Pathfinding & Innovation (AIPI) Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The memory solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. The Smart Manufacturing and AI team at Micron Technology is looking for an ambitious engineer (Member of Technical Staff | MTS) to deliver industry-winning Agentic AI solutions that power Micron’s dominance in the highly competitive memory solutions market. This role sits at the intersection of applied Agentic AI engineering and production systems work: you will architect autonomous AI Agents and the agentic and data pipelines that power them, build robust CI/CD deployment paths to Kubernetes and containers, and push the limits of agent performance profiling and evaluation to turn massive data and compute into measurable manufacturing impact. Qualified applicants will have experience across data/cloud technologies and systems engineering, with extensive practice modeling data, querying, and deploying scalable pipelines to execute AI agents. You will collaborate with Data Scientists, Data Engineers and expert users to build and deploy scalable Agentic AI solutions th

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for an AI Engineer to join our team. This is a Hybrid role, reporting to the Engineering Manager in the Product Operations department. We are seeking a hands-on AI Engineer to help scale the agentic layer of our AI Native - Product Operations Platform. In this role, you will design and build production-grade AI systems, reusable platform capabilities, and the engineering harnesses required to safely develop, evaluate, debug, and operate AI workflows at scale. As a pragmatic builder who understands modern AI systems in practice, you will translate ambiguous business needs into scalable technical solutions in a high-velocity environment. What you’ll do (Role Expectations) Build and scale the agentic layer of the AI Native - Product Operations Platform by designing production-grade AI systems, reusable platform capabilities, and reliable execution patterns Develop Agentic AI capabilities by applying p