Infrastructure Team Manager Jobs

Solution Architect Sigma Computing The SA role has evolved. Here’s the version we’re hiring for. The SA job in 2026 is not the SA job in 2023. Three things now sit at the center of how we evaluate this role. This hire has to do all three at a senior level, with the architectural depth to back it up. 1. Use AI every day to do the job better. If you are not using Claude, ChatGPT, Cursor, or equivalents to accelerate your account prep, architecture diagramming, prototype builds, RFP responses, and discovery synthesis, you are getting outworked by SAs who are. We expect this hire to treat AI tooling as default infrastructure, not novelty. Come with a point of view on what you run, why, and how you use it to compress weeks of work into days. 2. Sell AI into the account. Buyers want to talk about agents, MCP, A2A, context engineering, and which model is powering what. You have to be fluent. You know Sigma’s AI surface cold: Sigma Assistant in build, analyze, and plan modes, AI functions, input tables with LLM enrichment, MCP integration, and warehouse-native agent patterns. You can architect Sigma agents and warehouse agents into a customer’s stack and explain the tradeoffs to a head of data and a CISO in the same call. You also speak credibly about Claude, OpenAI, Gemini, and the broader stack the customer already runs. 3. Sell against AI. Every enterprise deal has AI competition in it. Sometimes it is Databricks Genie. Sometimes it is Snowflake Cortex Analyst. Sometimes it is a systems integrator pitching a bespoke agent built over the weekend. You know where each of these breaks at scale, where Sigma’s warehouse-native architecture wins on governance, freshness, and cost, and how to draw the line for a skeptical CDO without hand-waving. You can defend that position in an architecture review, on a security questionnaire, and across three follow-up calls. About Sigma Sigma is the AI runtime environment for the modern enterprise. Teams build apps, agents, an

Location : Come and join us in Hamburg or Berlin! Following Lyft’s acquisition of Freenow, we are looking for a Senior TPM to lead the technical workstreams that get us to Day 1 readiness — the period between signing and closing — and to set up the integration that follows. This is a high-stakes, high-visibility role reporting into the EU Tech Leader, with direct exposure to Freenow and Lyft leadership. You will be the single point of accountability for technical Day 1 readiness. That means making sure every employee, every office, and every critical system is ready to operate underFreenow by Lyft from the moment the deal closes — and that the integration stream is up and running the day after. You will also be the TPM accountable for the integration of future acquisitions Freenow makes. This is not a role for someone who wants to administer a project plan. You are expected to be technically credible, opinionated, and comfortable holding senior people to account across IT, Security, Infrastructure, Engineering, Legal, People, and Finance. You make decisions when others stall, escalate cleanly when you can’t, and keep the whole machine moving. YOUR DAILY ADVENTURES WILL INCLUDE: Day 1 readiness. Own the end-to-end technical readiness plan between signing and closing. Define what “ready” means, track every workstream against it, and call the go/no-go on technical readiness for Day 1. IT and workplace cutover. Coordinate identity and system access (SSO, IdP, mail, productivity suite, engineering tooling), hardware provisioning and re-imaging, and office setup including network, VPN, Wi-Fi, meeting rooms, and physical access. Make sure nobody shows up on Day 1 unable to work. Security and compliance posture. Partner with Security and Legal to make sure the technical environment meets the new shareholder’s requirements on Day 1 — access controls, data handling, audit trails, vendor relationships. Integration stream kickoff. Stand up the technical integration workstreams

Toradex is a global company strongly focused on engineering & technology. We’re powered by a diverse & uniquely gifted workforce. We pursue the best people to propel our innovative vision of embedded computing and IoT. If you’re interested in being a driving force at an agile technology company, engineering clever computing solutions & helping other companies bring their products to life, we should talk. Description We are looking for a DevOps Engineer to strengthen our cloud operations and engineering practices, with a focus on reliable website delivery, secure AWS foundations, and fast but controlled delivery of new services. The position combines AWS operations, infrastructure as code, CI/CD, automation, and pragmatic software engineering. The person should be confident working with services for edge delivery, compute, storage, databases, DNS, security, and observability without relying on manual console changes as the default operating model. The role also supports on-premises to cloud migration, global service optimization, and practical responses to increasing AI-driven traffic. We value candidates who can use modern AI-assisted development effectively to spin up proof-of-concept projects quickly, while still applying disciplined Git, review, security, and deployment practices. About you You enjoy building stable, secure, and maintainable infrastructure that supports business-critical services. You can work independently and take ownership of cloud environments, deployments, and operational improvements. You are comfortable balancing speed, reliability, cost, and security when making technical decisions. You communicate clearly with technical and non-technical stakeholders and explain trade-offs in a practical way. You document your work well and create clear runbooks and support material for future maintenance. You are methodical when troubleshooting incidents and stay calm when systems are under pressure. You are curious about modern traffic patt

Role: Application Reliability Engineer Location: Gurgaon Who we are Graviton Research Capital is a privately funded quantitative trading firm striving for excellence in financial markets research. We trade across a multitude of asset classes and trading venues using a diverse range of concepts, from time series analysis and stochastic models to machine learning and statistical inference. We analyse terabytes of data to identify pricing anomalies and drive innovation in financial markets. Key Responsibilities and Deliverables The ideal candidate will possess a strong background in technical support, with a passion for problem-solving and a commitment to excellence. As an Application Reliability Engineer, you will be responsible for: Monitor production services and respond quickly to alerts, incidents, and outages to ensure smooth operation and minimal downtime. Monitor trading systems and infrastructure., Triage issues across trading support services, databases, and infra; escalate and coordinate with the right owners, and drive root-cause analysis and ensure fixes are implemented for long-term stability. Serve as the first line of defense for trading operations. Proactively identify, address recurring issues, and build automation to reduce manual intervention. Improve observability by enhancing monitoring, logging, and alerting systems. Develop and maintain operational runbooks and SLO/SLA metrics. Eligibility and Required Skills Possess a degree in a highly analytical field, such as Engineering, or Computer Science 2-5 years of experience in Python, Shell/Bash scripting. Experience with Linux and shell/bash online tools. Hands-on experience with databases (SQL, NoSQL) Strong problem-solving and analytical skills Excellent communication skills Ability to remain calm and analytical under production pressure Good to have: Familiarity with monitoring/alerting stacks (Prometheus, Grafana, ELK, etc.) Familiarity with distributed messaging (Kafka) and caching systems (Red

JOB TITLE Data Reliability Engineer A CAREER WITH CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. What you’ll do Ensure smooth day-to-day implementation of a large research infrastructure and the timely delivery of comprehensive and error-free data to Cubist’s portfolio managers across the globe Serve as a frontline owner for mission-critical data ETL pipelines that power trading and investment decision-making, ensuring reliability, accuracy, and timeliness. Actively manage and resolve data incidents in a fast-paced trading environment, partnering closely with investment professionals, data scientists, and external data vendors. Design and build tooling, automation, and robust documentation to improve operational efficiency, scalability, and data quality across the platform. Play a hands-on role in daily data operations, including data validation, remediation, and enrichment, with opportunities to continuously improve and modernize workflows through engineering best practices. What’s REQUIRED Bachelor’s degree in computer science or a related field. Strong proficiency in SQL Server and Python programming, with experience in AWS and both Windows and Linux environments. Exceptional attention to detail with a strong appreciation for well-defined processes and systems. 3+ years of experience in a client-facing support or operations role. Excellent organizational, communication, and interpersonal skills. Commitment to the highest ethical standards About point72 Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Poin

About Prophecy Prophecy is building the next generation AI-powered data prep and analysis platform. Our platform enables business analysts and data teams to transform raw data into reliable, production-ready datasets and insights faster, using modern data infrastructure and AI-driven capabilities. We work with leading enterprises to simplify how organizations prepare, analyze, and operationalize data, while maintaining strong governance, security, and operational control. Our mission is to make it dramatically easier for organizations to turn complex data into trusted insights that drive decisions. About the Roles We are looking for a Director of Strategic Partnerships who can do both: drive revenue through Prophecy's partner ecosystem, and build an effective partner program. This is an early-stage, high-ownership motion, the playbook is still being written, and you'll have real influence over how we engage partners, what good looks like for partner-sourced pipeline, and how we build durable co-sell relationships with Snowflake, Databricks, GCP field and partner teams. You will sit at the intersection of sales, partnerships, and strategy, owning partner performance while building the programs and processes that scale it. You'll work directly with our AEs and SEs to bring partners into deals at the right moments, and you'll serve as the primary point of contact for our strategic cloud and ecosystem partners. What You’ll Own Partner Revenue & Pipeline Own and exceed partner-sourced and partner-influenced revenue targets on a quarterly basis Proactively generate pipeline through Snowflake, Databricks, and GCP field AEs and PDMs — building the relationships that produce qualified, sourced opportunities Drive joint account mapping and target account activation against Prophecy's ICP: enterprises running Alteryx on Snowflake or Databricks Activate co-sell motions through marketplace programs (GCP Marketplace, Snowflake Partner Network, Databricks

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Software Engineer, you will own the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Design and implement scalable backend systems for Federal customers using cloud-native AI infrastructure. Build features for agentic systems including multi-layered guardrails and data retrieval optimization. Develop data pipelines and machine learning infrastructure to make data sources accessible by agents. Collaborate with cross-functional teams to execute backend solutions for secure environments. Participate in customer engagements to understand requirements and deliver technical solutions. Define requirements with stakeholders and implement features until they are accepted. Contribute to the platform roadmap and product strategy for the Federal business. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers. Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. Direct the orchestration of asynchronous agent fleets to meet mission requirements. Lead customer engagements to translate mission needs into technical requirements. Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. Conduct technical reviews and identify risks within machine learning infrastructure and model serving. Drive the platform roadmap by providing technical specifications for Federal product offerings. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and contai

Software Engineer Argentina; Uruguay Software Engineer - Robotics & Autonomous Systems Scale's Robotics business unit is dedicated to solving the data bottleneck in Physical AI across Robotics, Autonomous Vehicles, and Computer Vision. In this role, you'll be a key contributor building production systems for robotics data collection, model training pipelines, and evaluation infrastructure. You'll have the opportunity to own critical parts of our robotics platform, work directly with cutting-edge robotics and AV customers, and shape the future of embodied AI systems. You Will: Own and architect large-scale data processing pipelines for robotics and autonomous vehicle datasets Build ML training and fine-tuning pipelines using Scale's robotics data Work across backend (Python, Node.js , C++), and frontend (React, TypeScript) stacks to build end-to-end solutions Develop tools and real-time systems for robotics data collection, teleoperation, model evaluation, data curation, and data annotation Interact directly with robotics and AV stakeholders to understand their technical needs and drive product development Design comprehensive monitoring and evaluation frameworks for robotics models and data quality Solving complex, late-stage industry challenges in concurrent and real-time robotic systems, with strict attention to timing constraints and data integrity. This often involves deep investigation, reviewing academic papers, and direct collaboration with robotics vendors Collaborate with ML engineers and researchers to bring robotics research into production Deliver features at high velocity while maintaining system reliability and performance Ideally, You Have: At least 6 years of high-proficiency software engineering experience, with a strong background in complex systems and the ability to independently research, analyze, and unblock hard technical problems. Strong programming skills in Python and TypeScript/Node.js for production systems Experience with React and m

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We are seeking a technical, data-driven Product Management leader to own CLEAR's Marketing Technology platform. This role is responsible for the systems, data, and measurement capabilities that power member acquisition from first touch through enrollment. You will own CLEAR's MarTech ecosystem, including attribution and tracking, audience data infrastructure, CRM and lifecycle marketing platforms, and the integrations that connect marketing signals to actionable insights. Partnering closely with Marketing, Engineering, and Data teams, you'll ensure CLEAR has the tools and intelligence needed to scale growth across paid, organic, and partner channels. What You'll Do: Own the vision, roadmap, and performance of CLEAR's MarTech ecosystem, including CRM, audience activation, tracking, attribution, and marketing data infrastructure. Build best-in-class measurement capabilities across paid, organic, and partner channels, creating a trusted source of truth for acquisition performance. Partner with Marketing to improve audience targeting, lifecycle messaging, SEO/SEM performance, and channel optimization. Drive strategy for audience segmentation, activation, suppression, and first-party data utilization using platforms such as Snowflake and Hightouch. Own the digital enrollment experience, ensuring it is optimized for conversion, personalization, and growth. Define success metrics, manage vendor relationships, and prioritize investments that maximize marketing effectiveness and ROI. What We're Looking For: 8+ years of Product Management experie

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

SonicWall is a cybersecurity forerunner with more than 30 years of expertise and is recognized as a leading partner-first company, ensuring our partners and their customers are never alone in the fight against cybercrime. With the ability to build, scale and manage security across the cloud, hybrid and traditional environments in real-time, SonicWall provides relentless security against the most evasive cyberattacks across endless exposure points for increasingly remote, mobile and cloud-enabled users. With its own threat research center, SonicWall can quickly and economically provide purpose-built security solutions to enable any organization—enterprise, government agencies and SMBs—around the world. For more information, visit www.sonicwall.com or follow us on Twitter , LinkedIn , Facebook and Instagram . As a Software Dev Senior Engineer , you will own the reliability, scalability, and operational excellence of our Cloud-based services. You will define and enforce reliability standards, drive the adoption of SRE practices across engineering teams, and build the systems and tooling that keep our production infrastructure healthy. We follow a DevOps model: Development and Operations teams are integrated, and the SRE function acts as the reliability layer — setting Service Level Objectives, managing error budgets, and continuously reducing toil through engineering. Key Responsibilities: Define, publish, and continuously refine Service Level Indicators (SLIs), Service Level Objectives (SLOs), and Service Level Agreements (SLAs ) for all critical services, partnering with product and engineering leadership. Own the error budget framework: track consumption, enforce error budget policies, and drive reliability investments when budgets are at risk. Lead the design and implementation of comprehensive observability platforms — metrics, structured logging, and distributed tracing — to ensure full visibility into pro

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. Partnerships Lead - Instawork Robotics Labs || Bengaluru, India (Extensive Travel) · Field & Growth Operations About IRL Researchers at UC Berkeley have identified a “100,000-year data gap” - the gulf between what trained AI language models and what physical robots actually have to learn from. Closing that gap is the defining infrastructure challenge of the physical AI era. IRL is Instawork’s answer to it. We deploy skilled workers into real commercial and residential environments - kitchens, warehouses, hotel floors, homes - to capture the high-fidelity task data that the world’s leading Robotics labs use to train their foundation models. Read more here . Instawork is building the data engine for the future of physical AI. To do that at scale, we need reliable, high-volume access to businesses across India whose skilled manual work becomes the training data for the next generation of robotics. We are looking for a Partnerships Lead to secure that access — both by hunting new opportunities directly and by brokering relationships with the people who already control access to hundreds of businesses: association presidents, lenders, government officials, and enterprise leaders. Your job is to convert both cold outreach and high-trust institutional relationships into onboarding pathways at scale. What You'll Do Broker access at scale. Identify, cultivate, and close relationships with high-leverage intermediaries — presidents of business associations, lenders, banks, politicians, civil servan

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. About IRL Researchers at UC Berkeley have identified a “100,000-year data gap” - the gulf between what trained AI language models and what physical robots actually have to learn from. Closing that gap is the defining infrastructure challenge of the physical AI era. IRL is Instawork’s answer to it. We deploy skilled workers into real commercial and residential environments - kitchens, warehouses, hotel floors, homes - to capture the high-fidelity task data that the world’s leading Robotics labs use to train their foundation models. Read more here . Role Overview We are building one of India's largest commercial video data collection networks . As a Zonal Data Captain , you will own the business pipeline for your assigned zone . Your primary responsibility is to find businesses, convert them for on-site video data collection, and keep the recording engine in your territory active every single day . You will spend your days in the field meeting business owners, converting them, and expanding into new towns mapped to your zone . Core Compensation & Target Fixed Salary: ₹25,000 / month Performance Incentives: Up to ₹95,000 / week* Core Target: 8 business conversions / day *Incentive Note: Incentives are performance-based and linked to verified conversions, recorded hours generated from your converted businesses, and quality/consistency of execution . All conversions and hours are subject to verification before payout . A detailed slab structure will be shared at the offer stage . What You'll Do 1. B

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. About IRL (Instawork Robotics Labs) Researchers at UC Berkeley have identified a “100,000-year data gap” - the gulf between what trained AI language models and what physical robots actually have to learn from. Closing that gap is the defining infrastructure challenge of the physical AI era. IRL is Instawork’s answer to it. We deploy skilled workers into real commercial and residential environments - kitchens, warehouses, hotel floors, homes - to capture the high-fidelity task data that the world’s leading Robotics labs use to train their foundation models. Read more here . What you’ll do Lead Workforce & Operations: Drive day-to-day workforce management for Clippers, Graders, Regraders, SMEs, and ICs across shifts/sites, optimizing staffing, capacity planning, and throughput against SLA targets. Implement Quality Systems & Methods: Maintain the QMS and apply structured methods (RCA, CAPA, FMEA, 8D, SPC) to address recurring defects, calibration drift, gold-sample injections, and consensus checks. Own SOPs & Process Standards: Build, version-control, and continuously iterate SOPs for existing and new program launches, ensuring floor adoption and structured QA onboarding/re-calibration paths. Bridge Cross-Functional Teams: Translate engineering data requirements into floor-executable QA criteria, report field issues back with evidence, and represent QA in program launches and crisis calls. Drive Data-Led Quality: Monitor and analyze key QA metrics—defect/reject rates, inter-grader agreement (ka