Ai Enterprise Architect in United States

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. Tenstorrent is seeking an Physical Design Engineer to lead cross-functional efforts to solve complex physical design challenges and develop end-to-end RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements. The engineer will architect, integrate, and deploy AI/ML-driven solutions into production physical design flows, creating custom CAD tools and partnering with internal teams and EDA vendors to drive next-generation, ML-enabled capabilities. This role is hybrid, based out of Santa Clara, CA or Austin, TX or Fort Collins, CO. 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 BS in Electrical or Computer Engineering (or equivalent experience) with 5+ years in Physical Design CAD methodology at advanced nodes. Proven track record improving PPA and/or runtime on high-performance, low-power taped-out designs. Hands-on with industry-standard EDA tools (e.g., Fusion Compiler) across synthesis, P&R, STA, signoff, and hierarchical flows. Strong Python/Tcl and data skills, with interest or experience in ML frameworks (PyTorch, TensorFlow), and the ability to drive complex projects independent

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. Our Tensix team is building custom AI compute cores, RISC-V CPUs, and chiplet-based architectures for datacenter, edge, and automotive AI. Design Verification Engineers on this team validate compute IP and subsystems and build scalable DV infrastructure to keep verification fast, automated, and production-grade. This role is hybrid, based out of Toronto, ON, Austin, TX or Belgrade, Serbia. 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 Experienced in modern verification methodologies with strong SystemVerilog skills and exposure to structured testbench development. Comfortable working from block-level to system-level verification and reasoning about microarchitecture behavior from specs and waveforms. Proficient in Linux environments with Python, or Bash scripting for automate builds, parse logs, manage CI pipelines. Skilled in coverage-driven verification and confident debugging across RTL, testbench, and workload scenarios. Motivated by AI hardware and eager to learn verification strategies for new architectures and domains. What We Need Contribute to verification of Tensix IP and subsystems from early planning through tape-out, owning cov

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. Tenstorrent licenses RISC-V and AI IP to customers who need hardened, PPA-proven deliverables on their target node and foundry. This role owns physical implementation of those IP blocks end to end, from synthesis through PnR, timing closure, and GDSII signoff, and directly determines how fast we can commit to a customer's timeline. This role is hybrid, based out of Toronto, ON; Austin, TX; or Belgrade, Serbia. 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 hands-on physical design engineer who owns blocks end to end, with a track record of block-level and IP tapeouts on advanced nodes. Driven by PPA outcomes, working closely with RTL owners to close critical paths and hit power budgets. Rigorous about signoff quality, because our IP ships to customers who integrate it without you in the room. What We Need BS/MS/PhD in EE/ECE/CE/CS with 5+ years of block-level or IP-centric physical design through tapeout. Expertise with industry-standard tools (Innovus, ICC2/FusionCompiler, PrimeTime) and scripting languages (Tcl, Python, Perl). Deep understanding of advanced node challenges, low-power design (UPF, power gating, multi-Vt, voltage sc

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. Our Tensix Team is building the future of AI compute with a ground-up architecture centered on scalable RISC-V processors. As we push performance boundaries, we’re reimagining the frontend of our RISC-V cores to deliver major gains in programmability, efficiency, and developer experience. This is a rare opportunity to shape the CPU architecture at the heart of our AI platform and lead one of the most strategic technical efforts at Tenstorrent. This role is hybrid, based out of Toronto, ON, Austin, TX or Santa Clara, CA. We welcome candidates at various experience levels. 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 Experienced Microarchitect: 10+ years of deep expertise in CPU performance modeling and microarchitecture design. AI Workload Expert: Deeply familiar with the computational and memory bottlenecks of modern AI workloads, particularly Large Language Models (LLMs). Hardware-Software Co-Designer: Driven to architect custom instruction set extensions and validate their performance gains against real-world workloads. Ways to stand-out: Familiarity with open-source RISC-V cores, AI-based agentic workflow experience What We Need Profile & Analyze: Dissect cutting-edge AI workloads to identi

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. Our IP delivery timelines are set as much by flow maturity as by design work. This role develops, deploys, and owns the RTL-to-GDSII methodology the IP physical design team runs on, so a new block, node, or customer variant starts from a working flow instead of a cold start. This role is hybrid, based out of Toronto, ON; Austin, TX, or Belgrade, Serbia. 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 physical design or CAD methodology engineer who has built flows that production teams depend on daily. Automation-minded, happiest when you are removing manual steps and making PPA exploration repeatable. Building with AI as part of how you develop flows, and opinionated about where LLMs and ML-driven optimization genuinely help versus where they do not. An effective partner to design teams and EDA vendors, and a clear writer who documents flows well enough that others can run them without you. What We Need An Engineer with 5+ years developing and supporting physical design methodology or CAD flows in production use. Expertise with industry-standard tools (FusionCompiler/ICC2, Innovus/Genus, PrimeTime, RedHawk) and scripting languages (T

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

About the Team pAGI Infra team builds and operates the systems that make large-scale model training and evaluation reliable, efficient, and easy to run. Our work spans distributed training infrastructure, inference and grading platforms, compute scheduling, and research tooling. We partner closely with researchers and engineering teams to turn new research needs into dependable infrastructure, improve GPU efficiency, and shorten the path from an experiment to a validated model. About the Role We’re looking for an AI Systems Engineer to help scale the infrastructure behind our training and evaluation workflows. You’ll own projects from identifying bottlenecks and designing solutions through deployment and operation. The work combines distributed systems engineering, performance optimization, and close collaboration with researchers. You might build a shared grading service, improve resource allocation across workloads, or bring a new training stack into production — directly improving how quickly and reliably research moves forward. In this role, you will: Build and operate infrastructure for large-scale training and evaluation, improving reliability, throughput, and resource efficiency. Develop shared inference and grading platforms with automated capacity management, health monitoring, and visibility into performance. Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads recover quickly from failures. Diagnose bottlenecks across training, inference, and orchestration, and work across teams to improve end-to-end performance. Build self-service tools, automated validation, and observability that help researchers launch experiments, diagnose issues, and compare results with less manual intervention. You might thrive in this role if you: Are excited about the potential of personal AGI and want to build the infrastructure that enables it. Have strong software engineering fundamentals and experience building or operating large-scal

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Baseten's Compute org is in hyper growth. As it scales, the systems and workflows that keep supply and demand balanced across our GPU fleet need to get more sophisticated, and this role exists to make sure they do. Compute sits at the center of how Baseten allocates, forecasts, and manages the capacity that powers every customer inference request. The team that supports this work, C3, runs on a mix of internal tooling, manual processes, and systems that haven't fully kept pace with the scale of the problem. This role exists to close that gap. You'll design, build, and ship AI-powered workflows that give the Compute and C3 teams real leverage, automating the manual, repetitive, and error-prone parts of the capacity lifecycle so the team can focus on judgment calls that actually need a human. We want someone who can walk in, audit what exists today, identify what's missing or broken, and start shipping fast. You know when to reach for an existing internal tool and when to build something custom in Claude Code. You think two to three steps ahead about how the thing you build today fits into the broader capacity systems architecture tomorrow. And you bring a point of view on our stack, on what we should be building, and on where AI can do something existing tooling simply can't. RESPONSIBILITIES Ship AI-powered workflows for Compute and C3 : build the agents and automations that give capacity analysts, ops leads, an

Coder is looking for an AI Enablement Engineer to help execute our Smart AI roadmap and make AI and vibe coding easier across the company. You’ll work directly with employees to understand what they’re trying to build, answer questions about Smart AI best practices, and remove the technical or process barriers getting in their way. You’ll also turn those needs into shipped improvements. That means building and refining Smart AI journeys, reusable skills, paved paths, and infrastructure enhancements, while partnering closely with the Smart AI Program lead on roadmap execution. You’ll also teach through office hours and sessions, but most of your time will be spent listening, building, troubleshooting, and improving the system around our internal AI community. What you’ll do here Act as a hands-on technical partner for Coder employees using Smart AI, helping them understand best practices, choose the right approach, and work through blockers. Meet with employees across the company to understand their needs, requirements, workflows, and impediments as they build with AI. Answer questions in Slack, meetings, and working sessions about Smart AI tools, models, prompts, harnesses, development environments, and recommended patterns. Identify recurring needs across our internal AI community and translate them into clear requirements for the Smart AI roadmap. Execute against the existing Smart AI roadmap by building and improving reusable journeys, skills, templates, system instructions, and other paved paths. Contribute directly to infrastructure enhancements that make internal AI development easier, more reliable, and more consistent. Build alongside users when useful, using tools like Claude Code and other AI-assisted development workflows to prototype solutions and validate new approaches. Help improve the dedicated development environment employees use for vibe coding, including integrations, connectors, APIs, model access, and supporting infrastructure. Turn one-off que

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. About the Role We are looking for an AI Agent Security Architect to function as the primary technical authority for Replit’s autonomous and AI agent security blueprint. In this critical role, you will design, implement, and maintain the runtime defense systems, guardrail frameworks, and sandboxing architectures that govern AI agents executing code, invoking tools, and reasoning across our platform. You will be a key technical contributor—leading high-impact AI security initiatives and bridging the gap between non-deterministic AI behavior and rigorous cybersecurity controls for both engineering and executive leadership. What You'll Do AI Agent Security Strategy & Technical Execution AI Agent Security Blueprint: Define the long-term vision and architectural patterns for securing autonomous agent workflows, Model Context Protocol (MCP) integrations, multi-turn reasoning loops, and multi-agent coordination. Runtime Guardrails & Policy Enforcement: Architect and deploy dynamic input/output guardrail systems, semantic firewalls, and real-time intent verification filters to prevent goal hijacking, system prompt leaks, and indirect prompt injections. Agent Execution & Tool Sandboxing: Partner with Infrastructure and AppSec teams to design secure, short-lived, micro-isolated environments (e.g., microVMs, WebAssembly, container sandboxes) where agents can dynamically execute code, run shell commands, and interact with host operating systems safely. Agentic Threat Modeling & Red Teaming: Conduct specialized threat modeling against non-deterministic systems. Lead automated and manual AI red-teaming initiatives to uncover vulnerabilities in RAG context pipelines, vector stores, and tool-calling interfaces. Identity

Job Details: Job Description: This is a high-visibility, commissioned sales leadership role within Intel's US Sales organization, specifically focused on our most disruptive AI-Native and Strategic CSP accounts. You will be the primary architect of Intel's relationship with industry titans who are redefining the boundaries of AI model training, AIaaS solutions and deployment at scale. This is not a traditional sales role. You will operate at the intersection of deep technical engineering and executive business strategy, ensuring Intel's silicon and software roadmap aligns with the world's most demanding AI-as-a-Service and SaaS platforms across on-prem, Tier1 CSP and NeoCloud environments. Key Responsibilities Executive Orchestration: Act as the One Intel lead, building deep-rooted partnerships with C-suite executives and Principal Engineers at world-class AI and SaaS firms. Technical Value Synthesis: Translate complex hardware architectures (CPU, GPU, Accelerator, Networking, and Packaging) into business outcomes for customers running massive-scale distributed training and inference workloads. Strategic Growth: Drive Intel's data-centric growth strategy by identifying and securing design wins within the core infrastructure of the world's leading AI models and solution providers. Cross-Functional Leadership: Partner closely with Cloud Solution Architects (CSAs), Intel Business Units, Cloud and OEM partners to influence future product roadmaps based on the unique needs of AI-native disruptors. Market Evangelism: Serve as a technical and business evangelist, articulating Intel's vision for the future of AI and compute infrastructure in a highly competitive landscape. <p style="text-align:inhe

Step into a mission where what you do truly matters! At Leidos, innovation is at the heart of everything we do. Powered by a team as diverse as it is talented, we're driven by a shared passion for delivering bold solutions that fuel our customers' success. We believe in empowering our people, giving back to our communities, and leading with sustainability. Every action we take is grounded in integrity and a steadfast commitment to doing what’s right—for our customers, our teams, and the world around us. Our Mission, Vision, and Values aren't just words—they're the compass guiding our journey toward a brighter future. If this sounds like the kind of environment where you can thrive, keep reading! Leidos is thrilled to share an exciting opportunity for a mission-focused Intelligence Analyst (AI/ML) at Joint Base Langley–Eustis in Hampton, VA! This is a chance to directly shape the next generation of Air Force intelligence professionals through cutting-edge AI/ML, data analytics, and automation training. Candidates must currently hold an active TS/SCI clearance . What You’ll Do: Help empower the ACC A2 mission by delivering high-impact instructional support: Assist in providing instructional support services that will allow the A2 staff to achieve its mission: Independently deliver and maintain formal classroom and virtual instruction on tool-agnostic AI/ML concepts, Large Language Models (LLMs), Robotic Process Automation (RPA), and advanced data analytics, ensuring established courseware remains current with standard DoD and IC applications. Execute tiered role-based training, adapting delivery to meet varying student proficiency levels—ranging from foundational AI/ML user adoption and awareness to intermediate prompt engineering and automated workflow creation. Instruct personnel on the underlying methodologies of AI/

Become a part of our caring community The Senior Full Stack Engineer Performs software engineering activities in all layers of the stack, from setting up the database to programming in the back-end and the appearance at the front-end. The Senior Full Stack Engineer work assignments involve moderately complex to complex issues where the analysis of situations or data requires an in-depth evaluation of variable factors. As Centerwell builds its AI engineering function from the ground up, we need a platform foundation strong enough to support everything that comes next. As Lead Full-Stack Engineer focused on platform and API engineering, you will design and build the service layer that connects AI capabilities, data systems, and product frontends—setting the standards for how services are built, secured, and operated across the team. You will work with meaningful architectural scope, making decisions that span API design, security patterns, and deployment practices. The platform you build will serve care teams and patients across hundreds of Centerwell clinics. If you want to build platforms that others build on—and do it in service of better primary care—this is the role for you. Key Responsibilities Platform and API Architecture: ** Design and lead development of core backend services, REST and GraphQL APIs, and service-to-service integrations that connect all layers of Centerwell's AI product stack. Security and Compliance by Design: ** Establish patterns for authentication, authorization, rate limiting, PHI access control, and audit logging. Ensure HIPAA compliance is embedded in platform design from day one—not bolted on after the fact. AI and LLM Integration Patterns: ** Define and implement reusable patterns for integrating AI capabilities into product

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . This role sits at the intersection of advertiser experience and ad creative, owning the tools and workflows that help advertisers create, manage, and optimize the right ad for the right Pinner at scale. You’ll shape how creative assets are uploaded, organized, and activated across campaigns, including new AI‑powered and automated solutions. Your work will directly impact how efficiently advertisers of all sizes can create on‑brand, high‑performing campaigns, and will be a key driver of Pinterest Ads revenue growth. What you’ll do: Lead end-to-end design for Merchant AI Assistant experiences across Pinterest Business Assistant workflows, including onboarding, catalog health, and Catalog Enhance. Define cohesive patterns that connect conversational AI with contextual product experiences, helping merchants understand priorities and complete

Senior Scientist – Physical AI for Surgical Robotics (Cambridge, MA) — Cambridge (US), Massachusetts, United States. Apply via Workday.