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Ai Senior Systems Engineer Jobs

10,000 active opportunities · Updated for October 2026

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Explore current ai senior systems engineer jobs. Use filters to narrow by work mode, employment type, experience and date posted.

V
Vanta
📍 United States• Full-time
1mo ago

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Vanta's Corporate Engineering team is the infrastructure layer that keeps 1,500+ people connected, secure, and moving fast. AI is now central to how that happens, and this role leads the team that owns the backbone underneath it. Corporate Engineering owns the shared AI platform for Vanta's internal systems: identity and access for AI tools, cost visibility and controls, sanctioned tooling and guardrails, and the enablement that helps people use those tools well. We do not own product AI, which stays with Engineering, and we do not replace the AI work happening inside individual departments. We build the engineering layer that makes all of it safer, cheaper, and better supported. The company has moved fast. AI assistant use is widespread across every function, MCP infrastructure is live and self-serve company-wide, internal apps ship on a hosted platform, and AI spend has grown to the point where attribution and guardrails genuinely matter. What does not exist yet is a single owner for that platform layer. That is this role. As Sr. Manager, AI Engineering, you will lead a small, senior team, write the charter for what Corporate Engineering owns versus enables, and build the platform that lets the rest of Vanta adopt AI quickly without accumulating cost, risk, or duplication. What you’ll do as a Senior Manager, AI Corporate Engineering at Vanta: Lead, coach, and grow a senior team spanning platform engineering and technical program management. Set clear direction, hold a high bar, and give the team explicit permission to push back with data. Own the AI access layer end to end: identity and authentication for AI tools, connector

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SA
16 days ago

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

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EA
16 days ago

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Senior Emulation Engineer Location: India - Remote Job Description: At EnCharge AI, we are building the next generation of AI compute silicon — purpose-built for high-performance, low-power, and scalable AI inference. As an Emulation Engineer, you will play a critical role in validating complex AI accelerator architectures on emulation platforms before tape-out. This position is ideal for someone passionate about bridging the gap between hardware and software in fast-paced, deep tech environments. Responsibilities: • Set up and maintain Siemens Veloce emulation and prototyping platforms • Adapt SoC designs for Emulation and Prototyping • Develop and debug emulation testbenches and system-level environments • Support pre-silicon validation, power/performance analysis, and early software bring-up. Participate in silicon bring-up and validation. • Collaborate with design and verification teams to isolate design issues and accelerate debug. • Optimize performance of the emulation workloads and reduce turnaround time. • Work with firmware/software teams to enable use of emulators for OS and driver testing. Required Background: • BS/MS/Ph.D. in EE, CS, or related field with 7+ years of SoC design experience. • Experience with emulation platforms (Veloce, Palladium, or ZeBu) and FPGA-based prototyping systems (proFPGA, HAPS, or Protium) • Experience with emula

pythongitai
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SA
Scale AI
📍 San Francisco• Full-time• From $180K/yr
16 days ago

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack—from React/TypeScript frontends to Python-based backends—while integrating with LLMs and machine learning systems. You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment. What You’ll Do Own major full-stack product areas , driving features from design through production deployment. Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness. Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components. Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences. Deliver experiments and new features quickly , maintaining high quality and tight feedback loops with customers. Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP. Adapt quickly —learning new technologies, frameworks, and tools as needed across the stack. Ideal Experience 5+ years of full-time engineering experience , post-graduation. Strong experience developing full-stack applications using React, TypeScript, and Python . Experience scaling or shipping products at high-growth startups . Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome). Proficiency with SQL and modern API development. Experience with Kubernetes , containerization, and microservice architectures. Experience working with at leas

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SA
Scale AI
📍 San Francisco• Full-time• From $216K/yr
16 days ago

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

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F
Forma.ai
📍 Toronto• Full-time• From C$190K/yr
15 days ago

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! About the Team We build enterprise software that helps organizations optimize sales performance and improve go-to-market agility. Our engineering organization includes multiple product application teams responsible for delivering core customer-facing capabilities. We are seeking Senior Backend Engineers to join our application teams. You’ll work alongside staff, senior, and early-career engineers to design, build, and scale backend systems that power enterprise-grade product workflows. This is an opportunity to work on complex product and data problems while contributing meaningfully to technical decisions, system quality, and team delivery. We are low on meetings and high on accountability. Most of the team is in the EST time zone, with a few located in AST, PST, and Central as well. What you’ll be doing You will play an important role in the continued evolution of our application stack. You will design and build backend capabilities for complex product workflows, contribute to system design discussions, and help ensure our systems remain maintainable, reliable, and scalable as we grow. As a Senior Backend Engineer, you are expected to operate with strong ownership and sound technical judgment. This includes identifying risks in the work you own, surfacing edge cases, asking thoughtful questions, and proposing improvements that strengthen the quality and reliability of the system. You will: Design and build backend services that power complex product workflows. Contribute to d

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F
Forma.ai
📍 Toronto• Full-time• From C$190K/yr
15 days ago

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! About the Team Engineers on this team build our rules-based calculation engine for processing sales commissions. This might sound simple if you have never been exposed to sales compensation plans, it is not. We are low on meetings and high on accountability. Most of the team is in the EST time zone, with a few located in PST and Central as well. We are still evolving many areas of the platform, which means there is meaningful room to improve the design, reliability, and scalability of the systems we build. What you’ll be doing Reporting to the Manager of Data Platform, you will play an important role in the evolution of our Spark-based data platform. You’ll design and build data-rich platform capabilities, contribute to system design discussions, and help ensure our data systems remain reliable, maintainable, and scalable as Forma grows. As a Senior Engineer, Data Platform, you are expected to operate with strong ownership and sound technical judgment. This includes identifying risks in the work you own, surfacing edge cases, asking thoughtful questions, and proposing improvements that strengthen the quality and reliability of the platform. You will: Design, build, and improve Spark-based data pipelines and platform services. Work with complex data models representing sales compensation plans, hierarchies, relationships, and enterprise datasets. Build reliable, deterministic data systems that customers and internal teams can trust. Improve testing, observability, data quality,

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About the Role REMOTE IN INDIA We're looking for a software engineer to build the Kubernetes-native control plane that provisions and runs our GPU inference fleet. You'll design a manifest-driven API where the inference team declares what they need, whether that's a cluster, a model deployment, or a capacity change, and our controllers handle the reconciliation, provider/runtime selection, and lifecycle management underneath, so the inference team never has to know or care which specific serving stack, scheduler, or hardware pool is doing the work. You'll also build the systems that keep the fleet efficient, not just running, including defragmentation and rebalancing logic that consolidates scattered workloads back into contiguous capacity, and scheduling/bin-packing improvements that push GPU utilization up without hurting latency. The core value we're after is decoupling the people building on top of the platform from the operational and runtime complexity underneath, while squeezing more usable capacity out of the same hardware. You'll build the controllers, reconciliation loops, and self-service surface (API/CLI, not tickets) that make that decoupling real, plus the event-driven health, remediation, and utilization systems that keep it running and efficient without a human in the loop. Strong candidates have hands-on experience with Kubernetes controller/CRD patterns, have built or operated a platform API that abstracts multiple backends behind one interface, understand GPU scheduling and capacity efficiency (fragmentation, bin-packing, right-sizing), and think about GPU infrastructure as software to be engineered. A product mindset - you've built internal platforms or APIs consumed by other engineering teams and care about the developer experience of what you ship. You build it, you own it. You are not only responsible for delivering the software but also for operating and supporting it in production. Responsibilities Build the provisioning state machine

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SA
Scale AI
📍 San Francisco• Full-time• From $288K/yr
16 days ago

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineering & Optimization Create sophisticate

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F
15 days ago

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! Senior Staff Backend Engineer About the Team We build enterprise software that helps organizations optimize sales performance, enabling go-to-market agility. Our engineering organization includes multiple product application teams responsible for delivering core customer-facing capabilities. We are seeking a Senior Staff Backend Engineer to join our application teams and help set technical direction across multiple domains within engineering. You'll work alongside staff, senior, and early-career engineers, and partner closely with engineering leadership to define, evolve, and scale the systems that power enterprise-grade product workflows. This is an opportunity to own complex, multi-domain technical problems and shape product direction beyond a single team. We are low on meetings, high on accountability. Most of the teams are in the EST time zone, but we have a few located in AST, PST, and Central as well. What you'll be doing You will play a pivotal role in shaping the technical direction of our application stack across multiple domains. You will lead development efforts for our most complex initiatives, the kind that span two or more teams or product areas, and serve as a technical benchmark for system design, code quality, and long-term maintainability. You'll operate at the intersection of data modelling, business logic, and enterprise-scale reliability, and your work will often set standards that neighboring teams adopt. This remains a hands-on

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SA
Scale AI
📍 San Francisco• Full-time• From $216K/yr
16 days ago

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

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SA
Scale AI
📍 San Francisco• Full-time• From $180K/yr
16 days ago

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. Our Approach As part of the interview process, you’ll be considered for opportunities across several teams within the GenAI Engineering organization, based on your interests, expertise, and business needs. Potential team placements include Allocation, Growth, Frontier Data, Trust & Safety, Pay, Operator, or Tasking Experience. Together, these teams power Scale’s AI data operations - from building high-impact datasets that push the boundaries of LLM capabilities, to optimizing contributor onboarding and incentives, to safeguarding data integrity through advanced trust, safety, and security measures. They work at the intersection of ML, operations, and analytics to ensure we deliver the highest-quality data at scale. Responsibilities: Design, build, and maintain robust, scalable systems across the full stack, including front-end, back-end, and infrastructure layers Implement high-impact features using modern technologies such as TypeScript, React, Node.js, MongoDB, Elasticsearch, and Temporal Collaborate closely with internal operators (your use

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Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for custom LLMs Upskilling and advisory services to spread the impact of AI As a Full Stack Software Engineer (Forward Deployed), you’ll collaborate directly with public sector counterparts to quickly build full-stack, AI applications, to solve their most pressing challenges and achieve meaningful impact for citizens. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Partner with public sector clients to scope, collect feedback and implement solutions for complex problems, including spending up to two weeks per month in client offices for feedback and delivery. Architect production-grade applications that integrate AI models with full-stack frameworks, managing everything from interactive UIs to backend APIs and systems. Deploy and manage infrastructure within cloud environments, ensuring the highest levels of system integrity, security, scalability, and long-term reliability. Contribute to core platform features designed to be reused across diverse international client use cases. Partner with design, product, and data teams to build robust applications aligned with the broader technical architecture. Ideally you’d have: Bachelor’s degree in Computer Science or a related quantitative field 5+ years of post-graduation, full-stack engineering experience with demonstrated proficiency in React (required), TypeScript, Next.js, Python, Node.js, PostgreSQL or MongoDB plus hands-on experience with Docker, Kubernetes, and Azure

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SA
Scale AI
📍 San Francisco• Full-time• From $216K/yr
16 days ago

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

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N
Nuro
📍 Mountain View• Full-time• From $160.4K/yr
1mo ago

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role As a Senior Software Engineer, Collision Avoidance Testing, you will work closely with the onboard autonomy, evaluation infrastructure, data science, operations, and simulation teams to evaluate the performance of the autonomous vehicle in collision avoidance scenarios. You will be responsible for identifying gaps in onroad and simulation tests, designing appropriate tests to fill those gaps, reviewing test outcomes, and iterating on test design. You will analyse the results, recommend product changes, and report on residual risk both to leadership and in the safety case. About the Work Using human benchmarks from naturalistic data, develop statistical models that drive strategic decisions as a function of test volume, system performance, and confidence level. Identify and design realistic scenarios to drive test coverage of collision avoidance scenarios and collision detection scenarios using replay simulations of logs an

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