Controls Engineer Jobs

CAPCO POLAND *We are looking for Poland based candidate. Capco is a fully independent, global management and technology consultancy. For 25 years we have combined innovative thinking with deep industry knowledge to deliver business consulting, digital transformation and technology services to Finance and Energy markets. Our collaborative and efficient approach helps clients reduce costs and manage risk and regulatory change while increasing revenues. We are thinkers, innovators, and disruptors. We are small enough to care but large enough to matter. As an IT Security Analyst , you will play a key role in supporting a large-scale Secrets & Credential Management initiative. You will analyze current-state environments, identify control gaps, and define robust, scalable security requirements. Working across technical and business teams, you will help ensure that sensitive credentials are governed, controlled, and aligned with regulatory and operational expectations. Key Responsibilities: Conduct end-to-end analysis of secrets and credential management practices across applications, infrastructure, and platforms Identify, classify, and document secrets, including ownership, usage, storage, lifecycle stage, and associated risks Assess control gaps (e.g., unmanaged credentials, hardcoded secrets, weak auditability) and define remediation approaches Define functional and non-functional requirements for centralized secrets management solutions Facilitate workshops with stakeholders to gather requirements, validate findings, and support governance activities Required Skills and Experience: At least 5 years of experience in a similar role. At least 2 years of experience in working with IAM projects. Experience in IT security analysis, security requirements engineering, or security governance within complex environments Strong understanding of IAM, PAM, least privilege, and secure access governance principles Knowledge of credential types (passwords, SSH

SOBRE A CAPCO A Capco é uma consultoria global de tecnologia e negócios, focada no setor de serviços financeiros. Somos apaixonados por ajudar nossos clientes a ter sucesso em um setor em constante mudança. Estamos prospectando profissionais para vagas de Serviços de Planejamento de Operações de Comissionamento e Descomissionamento em Equipamentos Submarinos. Coordenar no Centro Integrado de Operações Submarinas (CIOp-SUB) as atividades referentes ao planejamento e prestar suporte técnico para escopo de serviço às gerências de projetos da SUB nas operações com equipamentos submarinos de todos os processos envolvidos. Emitir Relatório de Detalhamento técnico na fase de planejamento de operações de equipamentos submarinos de comissionamento e descomissionamento em modelo definido . Negociar com os integrantes do CIOp-SUB a inserção/retirada/postergação das operações programáveis da SUB/SSUB. Emitir Relatório Semanal de Pendências Críticas. Atualizar as restrições e marcos operacionais dos processos de Comissionamento e Descomissionamento no Sistema (sistema utilizado durante vigência do contrato). Participar e/ou coordenar as reuniões de planejamento externas prestando suporte técnico e dados de planejamento operacional. Realizar detalhamento técnico das ordens de serviço no sistema definido. O detalhamento técnico é considerado a elaboração de análise prévia da operação e inserção de documentação para execução de operação seleção de recursos necessários para atividade offshore. Conhecimentos e Habilidades Esperados: Ferramenta de planilha eletrônica (Pacote Microsoft Office – Excel) com habilidade para geração de tabelas e gráficos dinâmicos. Domínio Microsoft Power BI, Domínio do SAP: módulos de materiais (MM) e de manutenção (PM) e Sharepoint. Escolaridade - Capacitação: a) Formação Técnica em Mecânica, Eletromecânica, Controle e Automação ou Automação Industrial expedido por instituição de ensino reconhecida pelo Ministério da Educação. b) Regis

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. As a Datacenter Liquid Cooling Architect, you will define, design, and architect next-generation liquid cooling infrastructure for Tenstorrent’s large-scale AI training and inference clusters. You will partner with systems engineering, mechanical engineering, software, and cross-functional design teams to develop chassis-, rack-, and cluster-scale cooling solutions, including CDU integration, telemetry and control, leak detection, and resilient operating strategies. This role will help shape reliable AI datacenter architectures and deployments for both internal and external customers. This role is on-site, based out of Toronto, Canada, Austin, Texas or Santa Clara, California. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A datacenter and system thermal design professional with 10+ years of experience architecting cooling infrastructure for complex computing environments. An experienced liquid cooling architect who can design chassis- and rack-scale solutions for large AI training and inference clusters. A systems thinker who understands how mechanical, electrical, software, facility, and systems engineering decisions come toge

OUR MISSION At Redwood, we empower our customers with lights-out automation for their mission-critical business processes. ABOUT US Redwood Software is the leader in full stack automation fabric solutions for mission-critical business processes. With the first SaaS-based composable automation platform specifically built for ERP, we believe in the transformative power of automation. Our unparalleled solutions empower you to orchestrate, manage and monitor your workflows across any application, service or server — in the cloud or on premises — with confidence and control. CORE VALUES One Team. One Redwood Make Your Own Weather Obsess over Customer Success Work the Problem Be Curious Own the Outcome Respect Each Other YOUR IMPACT We are looking for a Principal Engineer, Products & Platforms to join our Product engineering team to provide technical leadership across Redwood’s Workload Automation Platform, defining architecture, driving modernization, and influencing engineering strategy across multiple teams. You will be instrumental in the design, development, and enhancement of our platform, building high-quality, scalable, and secure software that powers enterprise data exchange for more than 1,000 customers worldwide. As a Principal Engineer, you will: Technical Leadership & Architecture: Define the path forward for complex engineering problems, establish best practices, lead design review and technology decisions, and mentor the team to excel, while driving the architecture, security, compliance, and observability of our Java/Spring Boot microservices. Platform and Infrastructure Ownership: Drive the deep understanding, architecture, and evolution of our core platform and infrastructure, focusing on resilience, communication between components, and scalability. Cross-Team Collaboration: Facilitate and drive cross-team collaboration with Product, QA, and other engineering groups to ensure end-to-end alignment and successful product delivery. AI Integration:

Experience 1-2 years Python Programming : Strong foundational skills in Python. Automation : Ability to automate tasks with Python scripts. Web Development : Basic knowledge of Flask or Django for building web applications. Database Management : Understanding of SQL and experience with databases like MySQL or SQLite. Version Control : Familiarity with Git for code management. Data Analysis : Experience with libraries like Pandas and NumPy. Testing : Basic knowledge of writing unit tests. Problem-Solving : Ability to troubleshoot and solve coding issues. Basic DevOps : Introduction to CI/CD tools and processes. Communication : Good verbal and written communication skills.

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Data at Brex The Data organization develops infrastructure, statistical models, and products using financial data. Our Scientists and Engineers work together to make data —and insights derived from data — a core asset across the company. Our work is ingrained in Brex’s decision-making process, in the efficiency of our operations, in our risk management policies, and in the second-to-none experience we provide our consumers. What You’ll Do Our Data Scientists are responsible for the entire model development lifecycle, from conception with stakeholders, through model development and productionization, to following through to see that the desired business impact is achieved — including circling back with stakeholders to make product or strategic decisions. Responsibilities Drive Data & AI solutions from inception to deployment to efficiently manage risk and/or improve customer experience. Be responsible for the full machine learning

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll automate the integration of new capacity from a growing set of hardware providers; from auditing and benchmarking hosts and clusters, to maintaining our machine images, configuring GPUs, RDMA, networking, and storage, and getting machines into production. You'll build the automation that keeps the fleet healthy without human intervention: detecting bad GPUs, thermals, and disks. You'll dig into whatever is between the hardware and the software that runs on

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll own the full lifecycle of a machine, from accepting and benchmarking new hardware from a growing set of providers, to network bring-up, kernel and image management, GPU and disk health tracking, and automated remediation of unhealthy hosts. You'll manage a team of 3–8 engineers while staying hands-on across the stack which involves BMCs, firmware, PXE, bootloaders, Linux networking, drivers, and distributed control-plane services, and you'll shape our long-

DataHub is an AI & Data Context Platform adopted by over 3,000 enterprises, including Apple, CVS Health, Netflix, and Visa. Innovated jointly with a thriving open-source community of 13,000+ members, DataHub's metadata graph provides in-depth context of AI and data assets with best-in-class scalability and extensibility. The company's enterprise SaaS offering, DataHub Cloud, delivers a fully managed solution with AI-powered discovery, observability, and governance capabilities. Organizations rely on DataHub solutions to accelerate time-to-value from their data investments, ensure AI system reliability, and implement unified governance, enabling AI & data to work together and bring order to data chaos. About the Role We're seeking an experienced DevOps/ Site Reliability Engineering (SRE) Engineer to join DataHub and drive the reliability, scalability, and operational excellence of our platform offerings. In this role, you'll work on technical initiatives across DataHub Cloud and our emerging enterprise deployment solution, which provides customers with enhanced control and flexibility for running DataHub in their preferred environments. Key Responsibilities Enterprise Platform Development: Partner with product and engineering teams to influence the development of advanced deployment capabilities. Collaborate with cross-functional teams to help build systems for seamless installation, upgrade, and rollback processes across various environments. Influence the design and help implement comprehensive monitoring and health check systems for distributed deployments. Partner with engineering teams to help develop self-healing and automated remediation capabilities. Platform Reliability and Operations: Establish and maintain SLAs/SLOs for both cloud and enterprise offerings. Lead incident response and post-mortem processes to drive continuous improvement. Optimise system performance, capacity planning, and cost efficiency. Work closely with product, engineerin

B2B go-to-market software has historically been where design ambition goes to die. The tools are powerful but joyless. Dense, generic, admin-heavy, and built for process more than delight. Meanwhile, the best product companies have raised everyone’s expectations for what business software can feel like: fast, opinionated, elegant, and genuinely useful. AI gives us a chance to rebuild the category from first principles. Mutiny is building the agentic GTM platform that helps revenue teams create the work they need to win. Sellers and marketers should not have to wait on five internal teams to move a deal forward. They should have a bench of AI teammates that understands the account, knows what good looks like, and gets sharper every week. We’re looking for a founding staff designer to define what that feels like. This is not a role where you plug into a mature design system, clean product rituals, or a settled category. You’ll help invent the product language for AI-native GTM software: the interaction model, the creative standards, the feedback loops, the system, and the taste bar for what the agent produces. The design problem Our job is to make AI output that a great seller, marketer, or designer would actually be proud to put in front of a million-dollar account. That requires more than a chat box. It requires data, memory, taste, brand intelligence, workflow design, and a UI simple enough for every rep to use daily but powerful enough to support an entire revenue motion. Some of the questions you’ll help answer How should a seller direct an agent without becoming the agent’s project manager? How do we make generated work feel on-brand without making it dull? What does editing look like when the object is not a static page, but an intelligent system that can regenerate, revise, explain, and learn? How do we give users confidence and control without burying them in settings? How do we turn taste into a system the product can improve over time? What you’ll work on P

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Most of the value of owning a model shows up at serving time. We're building a platform that covers the whole life of an LLM -- train it, deploy it, observe it -- and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. What you'll do: Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spik

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustnes

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. Replit is the fastest way to turn ideas into software. With Replit Agent, anyone can build and ship a real application in natural language, without setting up a single tool. We've grown explosively, from $2M to $400M+ revenue in under a year, with a global community of 60+ million users, and Replit Agent is now one of the fastest-growing products in history. That same wave is now hitting the enterprise. Companies like Visa, Ernst & Young and Comcast are rolling Replit out to thousands of employees so finance teams, operations leads, and product managers can build without waiting on an engineering backlog. When a company puts Replit in the hands of thousands of employees, they're trusting us with their data and their workflows. That trust has to be earned: SSO and SCIM that just work, governance their security team will sign off on, and real control over where their apps run and how their data is handled. Getting this right is what turns a pilot into a company-wide standard, and it's one of the biggest levers on Replit's next phase of growth. About the Role We're hiring a Staff Product Manager to own Replit's enterprise product end to end. We've built one of the best coding agents in the world. The work now is making it just as powerful inside a big company, where putting it in front of every non-technical employee unlocks enormous leverage. That means extending what Agent can do in an enterprise context and building the platform that lets large organizations adopt it safely and at scale. This is a role with unusual leverage. We're still early in our enterprise journey but the traction is remarkable, which means most of the platform is still to be built and you'll have an outsized hand in shaping it. You'll decide w

Lead - Field instrumentation Engineer AHP and Water circuit (BOP) This role is responsible to manage the continuous availability and reliability of Control & Instrumentation (C&I) systems for the Ash Handling Plant (AHP) and water treatment systems through regular maintenance, system backups, and technical audits. This role involves managing business associates and ensuring adherence to budgets for optimal system performance. Source: Adani Group | Job ID: 51391

Job Description (JD) for MEP Engineer - Electrical Lead Projects & Site Integration. Experience Minimum 8 to 12 years of relevant experience in industrial pharmaceutical FMCG chemical manufacturing or process industry projects. Proven experience in handling electrical systems control systems for greenfield and brownfield projects. Experience in project execution commissioning and plant integration activities. Technical Competencies Electrical power distribution systems (HT/LT) Transformers switchgear MCCs PCCs UPS and DG systems Load calculations and power system studies Earthing and lightning protection systems Electrical safety standards and statutory compliance FAT SAT commissioning and start-up support Technical Bid Analysis (TBA) Vendor and contractor management AutoCAD and electrical drawing review Project planning and execution methodologies Excellent stakeholder management and communication skills Problem-solving and troubleshooting mindset Result-oriented with strong project ownership Effective planning organizing and execution skills Address: D-3/CL, MIDC Industrial Area,Turbhe, Navi Mumbai. 400705 Facility: ZOETIS PHARMACEUTICAL - NAVI MUMBAI Qualification: Post graduate Experience: 8 - 12 years Source: Sodexo India | Job Code: IJP575825