Software Engineer Aim Virtualization Jobs

We are seeking a highly versatile Sensor & Hardware Safety Engineer to bridge the gap between rigorous hardware reliability and real-world system behavior. In this hybrid role, you will be responsible for 50% hardware-level Functional Safety (ISO 26262) and 50% system-level sensor safety (SOTIF / ISO 21448). You will ensure that our custom hardware meets strict ASIL compliance while guaranteeing our advanced sensor suites (Cameras, LiDAR, Radar) operate safely through perception edge-cases and environmental challenges. In This Role, You Will: Evaluate supplier technical documentation for advanced imagers, microprocessors, and SoCs to verify SEooC and AoU alignment. Assess vendor deliverables to guarantee ASIL standards are met for firmware/software maturity and diagnostic systems. Execute board-level FMEDA for sophisticated integrated circuits, including FPGAs and microcontrollers. Partner with Software, FW, and EE departments to define architectural requirements that enhance diagnostic monitoring. Support the V&V team in developing SOTIF-compliant simulation and physical test protocols for edge-case scenarios. Qualifications Minimum of a B.S. in Automotive, Robotics, Aerospace, or Electrical Engineering. At least 3 years of professional experience involving board bring-up, silicon validation, or hardware design. Understanding of SOTIF and ISO 26262 safety protocols. Strong interpersonal and professional communication capabilities within a collaborative environment Bonus Qualifications ISO 26262 professional certification (CFSP or CFSE). Background in automotive-grade hardware validation and design. Experience utilizing traceability platforms like JAMA or Polarion. Familiarity with industry standards including IEC 61508, DO-254, and DO-178C during board bring-up.

About Zinnov Zinnov is a global management consulting firm that helps organizations make decisions that actually get used — and deliver results that matter. For over two decades, we’ve partnered with leading enterprises, high-growth technology companies, and investors to answer some of the toughest questions they face: Where should we invest? How do we scale globally? What capabilities will win in the next decade? Our work shapes market entry strategies, global operating models, M&A decisions, and long-term growth bets. We’re known for being data-led, execution-focused, and outcome-driven — not opinion-heavy slideware. At Zinnov, how you work matters as much as what you deliver. We value independent thinking, crisp communication, and early ownership. With 450+ professionals across 10 global offices, we work across industries including Digital Services, ER&D, Enterprise Software, Semiconductors, Healthcare, BFSI, Automotive, Media & Telecom, and Private Equity. Zinnov isn’t for everyone. It’s for people who want steep learning curves, honest feedback, and the chance to see their work influence real business decisions — not just presentations. About the Role As a Senior Data Engineer , you will own the data foundation of Zinnov’s GCC Intelligence Platform—building reliable multi-tenant pipelines and KPI-ready datasets across Finance and Hiring domains. Your work enables downstream dashboards and AI agents to operate on clean, reconciled, governed data. What You’ll Do Data Pipelines & Medallion Architecture Build andmaintainingestion pipelines from source systems (e.g., Dynamics, Workday, Airtable, SFTP feeds). Design and implement Medallion pipelines (Bronze → Silver → Gold) across Finance and Hiring data. Build reconciliation and gating logic to ensure only validated data reaches Gold. Multi-tenant Data Modeling Design multi-tenant PostgreSQL schemas with row-level s

About Zinnov Zinnov is a global management consulting firm that helps organizations make decisions that actually get used — and deliver results that matter. For over two decades, we’ve partnered with leading enterprises, high-growth technology companies, and investors to answer some of the toughest questions they face: Where should we invest? How do we scale globally? What capabilities will win in the next decade? Our work shapes market entry strategies, global operating models, M&A decisions, and long-term growth bets. We’re known for being data-led, execution-focused, and outcome-driven — not opinion-heavy slideware. At Zinnov, how you work matters as much as what you deliver. We value independent thinking, crisp communication, and early ownership. With 450+ professionals across 10 global offices, we work across industries including Digital Services, ER&D, Enterprise Software, Semiconductors, Healthcare, BFSI, Automotive, Media & Telecom, and Private Equity. Zinnov isn’t for everyone. It’s for people who want steep learning curves, honest feedback, and the chance to see their work influence real business decisions — not just presentations. About the Role As an Agent / AI Engineer , you will build the AI layer of the GCC Intelligence Platform—the conversational agent users interact with. You will own grounding, retrieval, persona routing, session state, and permission-aware querying so the agent stays accurate, secure, and tenant-safe. What You’ll Do LLM & Agent Integration Integrate LLM APIs (e.g., AzureOpenAIor equivalent) for conversational workflows. • Build a grounding layer that anchors responses to real platform data (not model guesses). • Maintain prompt templates across multiple personas and use-cases. Retrieval, Permissions & Security Boundaries Implement intent classification and persona routing to the right KPI views. • Build the API

About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Over the past few years, development of LLMs has evolved at a rapid pace. It’s not enough for our customers to just “set it and forget it” when it comes to AI software. Truly successful AI Agents require hands-on execution, rigorous iteration, and deep technical delivery to reach enterprise-grade performance. We’re creating an Agent Deployment Engineering Org : a specialized technical delivery team responsible for end-to-end execution of AI agent builds. Agent Deployment Engineers own the hands-on work required to deliver best-in-class agents—writing and configuring key components, validating integrations, and ensuring agents perform reliably at scale. This team brings greater specialization and focus to build quality. Agent Deployment Engineers are technical and customer-facing: you’ll interface with senior technical stakeholders on the customer side while also going deep on agent configuration and build execution. About the Role As an Agent Deployment Engineer, you will be responsi

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. Are you a digital transformation leader ready to architect the AI-driven future of the Energy sector? This is not a standard process optimization role. We are looking for a Lead Value Partner to own customer success and drive high-stakes SaaS and AI adoption across top-tier O&G enterprise accounts. You will serve as the strategic bridge—translating complex business needs into technical strategy. As a trusted advisor to C-suite executives (COO, CFO, CTO), you will blend deep operational Oil & Gas DNA with elite management consulting and an AI-first mindset to realize maximum customer value. The Impact You Will Drive Value Architecture: Translate executive priorities into AI use cases (optimization, maintenance, decarbonization) and Value Realization Frameworks. Solution Blueprints: Architect scalable, end-to-end data flows to resolve complex operational bottlenecks (refinery, pipeline, reservoir). Financial Quantification: Build data-backed business cases driving $10M+ in CAPEX/OPEX savings. Executive Advisory: Deliver high-stakes value narratives to C-suite stakeholders and supermajor leadership to accelerate software pipelines. Process Transformation: Automate field-to-back-office workflows using Master Black Belt methodolo

HackerRank helps companies like NVIDIA, Amazon, and Microsoft hire and upskill the next generation of developers based on skills, not pedigree. Our platform is trusted by over 2,500 of the world’s most innovative companies to build strong engineering teams ready for what’s next. Software has entered an era where humans and AI build side by side. As this shift accelerates, the definition of strong technical talent is changing. We give companies better ways to identify and invest in next-generation skills. People at HackerRank care deeply about the impact of their work and sweat the small details so our customers can be wildly successful with products they genuinely love to use. We move with urgency and believe great outcomes come from high standards. About the role Hiring is one of the most consequential decisions a company makes. 3,000+ enterprises rely on HackerRank to get it right. We are now reinventing how that works for the agentic era. The ML systems that power this platform are not auxiliary features. They are the product. Open Problems The agentic era is reshaping every layer of the hiring stack. These are some of the core problems you'll be working across, none of them fully solved. Chakra: Building an autonomous AI interviewer that conducts, adapts to, and evaluates technical interviews end to end. Integrity: Detecting fraud and suspicious behavior across multiple signal types. The ways candidates game assessments change frequently, and the models need to keep up. Evaluation: Measuring technical skill in a world where AI writes the code. The old proxies no longer hold and the new ones have not been defined yet. Your focus will shift across these depending on where the highest-leverage work is at any given time. What you will do Design and ship production ML systems across Chakra, integrity, and evaluation domains. Own the full ML lifecycle: problem framing, data strategy, experimentation, deployment, and iteration. Build evaluation infrastructure and bench

About the role As a Forward Deployed Engineer (FDE) focused on Inference & Post-Training, you will be a hands-on technical partner to our most strategic customers — production AI teams looking to leverage high quality models and do inference at scale. For us, FDE is not a replacement for a Solutions Architect; you will partner with our SAs as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment. As key contributors to both the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption, and guide tailored optimization efforts — directly impacting customer success, company growth, and the hardening of our core platform. Responsibilities Inference Engine Optimization: Select, configure, and optimize inference engine based on hardware, model architecture, and workload profile Configuration & Performance Tuning: Develop configuration updates to win critical POCs, benchmarks, and optimize customer deployments; tune KV cache, apply speculative decoding, determine optimal tensor parallelism, and determine quantization strategy to hit throughput and latency targets. Post-Training & Fine-Tuning: Drive hands-on RL training runs and optimize system design; guide customers through LoRA, SFT, DPO, RLHF, and GRPO pipelines from experimentation through production. Strategic Customer Alignment: Act as the primary technical point of contact for aligned strategic accounts — monitoring and optimizing endpoint configurations, helping customers get the most out of the platform, and collaborating to ensure we hit critical milestones. Opinionated Onboarding: Establish direct alignment with strategic customers at onboarding; ensure the right inference and post-training configurations are in place from day one to improve time-to-value. Product Feedback Loop: Directly influence our software and model roadmap by surfacin

About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team We are a brand new team, working quickly to accelerate Stripes engineering productivity by effectively deploying LLM agents and tools to automate large swaths of the engineering workflow. We’re a cross-continent team, spanning North America and Europe - filled with high agency engineers with strong product perspectives. Some examples of what we work on: here and here . What you’ll do You will build the next generation of internal AI coding tools and platforms, to massively accelerate Stripe’s engineering productivity safely and with a clear focus on our users’ needs. Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements We’re looking for someone who has: Strong software engineering skills and ability to write high quality code at high velocity 2-5 years of professional hands-on software development experience, able to write well-factored algorithms and have experience with commonly used data structure and algorithms Hands on experience building tools or platforms used by other engineers or internal users Strong collaboration skills, can work across workstreams within your team and contribute to your peers’ success Customer obsession, ability to articulate and represent customer experience in various forums to drive the right outcome Have t

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Pure Storage is seeking a full-time Principal Hardware Engineer working as part of our Hardware Development Team. In this position, you'll be working to define the technical direction of our next-generation hardware platforms. You’ll work closely with Architects, Engineering, Operations, OEM/JDM Partners and Support & Escalation Teams. You'll be responsible for the future of Pure’s high performance storage systems, acting as the primary subject matter expert for system hardware across executive, product, and client interactions.. WHAT YOU'LL DO Define system-level hardware architecture for FlashBlade, including compute, memory, interconnect, storage, power, and thermal design. Translate product requirements and customer needs into clear technical specifications and design trade-offs. Evaluate and select key components, technologies, and vendors, and lead make-vs-buy decisions. Drive architecture reviews and design reviews, and ensure designs meet performance, reliability, and compliance targets. Partner with firmware and software teams to define hardware/software interfaces and optimize the full stack Track emerging technologies and industry standards, and shape the long-term hardware roadmap. Work with manufacturing and supply chain on DFM/DFT, yield, cost reduction, and component risk. Strong understanding of X86 architecture and proven design track record Solid understanding of Major Bus

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 a SoC Physical Design Verification Engineer to drive full-chip signoff and ensure manufacturable, high-quality silicon across advanced technology nodes. You’ll lead physical verification closure (DRC, LVS, ERC, etc.), debug issues using standard industry PV tools, and collaborate across RTL, PD, CAD, and packaging teams to achieve successful tapeouts. If you thrive in a fast-paced environment and enjoy solving complex challenges in cutting-edge silicon, we’d love to hear from you. 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 A seasoned engineer with a strong background in CPU/IP/SoC physical verification and tapeout closure. A hands-on problem solver who excels at debugging and driving signoff through complex verification flows. A collaborative team player who works effectively across RTL, PD, CAD, and foundry interfaces. A mentor and technical leader passionate about building efficient, manufacturable silicon. What We Need BS/MS in Electrical/Electronics Engineering (or related) with 7–14 years of hands-on CPU/IP/SoC physical verif

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 to ship AI products. THE ROLE As an OS / K8s Systems Engineer at Baseten, you’ll build the automation and systems that turn raw GPU hardware into production-ready compute. From provisioning to orchestration, you’ll own the software layer that makes our infrastructure reproducible, scalable, and reliable across data centers. This is a senior, hands-on role focused on building systems not operating them. You’ll work close to the metal designing OS images, building provisioning pipelines, and automating cluster bring-up from scratch. Your work will define how quickly we can turn new capacity into usable compute. EXAMPLE INITIATIVES Zero-to-cluster automation Build workflows that take new hardware from unprovisioned to fully operational cluster. Provisioning systems Design PXE-based or equivalent systems for imaging and lifecycle management. Reproducible infrastructure — Ensure clusters deploy consistently across data centers. RESPONSIBILITIES Own the end-to-end automation of cluster bring-up and lifecycle management. Build and maintain OS images, provisioning systems, and configuration pipelines. Deploy and operate cluster orchestration platforms (Kubernetes, Slurm, or similar). Design systems for reproducibility across sites and hardware generations. Automate upgrades, rollouts, and failure recovery. Optimize system performance, including GPU utilization and networking. Partner with hardware and network teams to validate and improve system b

Here at Datadog, we think about offensive security a little bit differently. We embrace automation and AI to run adversary simulations continuously across a massive cloud-native environment, and we expect our offensive engineers to build the tooling that makes that possible. We're looking for a Senior Security Engineer who can execute sophisticated red team operations, write the code that scales them, and take an AI-first approach to offensive security engineering. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Plan and execute red team engagements end-to-end, simulating real-world threat actors across cloud infrastructure (AWS, GCP), Kubernetes, CI/CD pipelines, and corporate environments Build and maintain custom offensive tooling, automation frameworks, and engagement infrastructure, treating offensive operations as a software engineering problem Develop custom payloads and evasion capabilities tailored to Datadog's environment and modern defensive controls (EDR, SIEM, network monitoring) Improve the efficiency of offensive operations through thoughtful use of automation and AI, accelerating reconnaissance, vulnerability analysis, and reporting workflows Partner with the Detection & Response team on purple team exercises to validate detection logic, improve alert fidelity, and influence threat models Translate offensive findings into concrete improvements by working directly with defensive security and engineering teams to close gaps Who You Are: You have 5+ years of hands-on experience in offensive security (red teaming, penetration testing, or adversary simulation) with a track record of operating against mature, well-defended environments You write production-quality code (Python, Go, or similar), can build your own tools, and automate your w

Title: Senior AI QA Engineer Location: Bengaluru (Bangalore) Opportunity: As a Senior AI QA Engineer for our Precision Patient Care Pipeline , you will go beyond traditional functional testing. You will be responsible for building the framework that ensures our clinical insights are accurate, safe, and reliable. This role requires a unique blend of high-level software testing and data engineering to validate complex, non-deterministic medical outputs using a hybrid of automated grading methodologies . Key Responsibilities: Architect Multi-Layered Validation Frameworks: Design and implement structured testing strategies that combine deterministic checks, semantic similarity metrics, and model-based evaluations. Automated Model Grading: Develop systems to evaluate clinical pipeline outputs for faithfulness, safety, and hallucination detection using various automated scoring techniques (e.g., BERTScore, ROUGE, or custom heuristics). Vibe-Driven Development: Leverage agentic AI tools to rapidly prototype complex test harnesses, "red-team" clinical logic, and build internal validation utilities at high velocity. Data Pipeline Integrity: Execute integration and regression tests for data-heavy backend processes, ensuring medical data remains consistent from ingestion to insight generation. Collaborative Strategy: Work closely with Data Scientists and Product Managers to define "Ground Truth" datasets and clinical evaluation rubrics. Root Cause Analysis: Deep-dive into complex system failures to identify whether issues stem from code logic, data drift, or model behavior. Requirements: 6+ years of technical experience in Quality Assurance, with a strong focus on system architecture and backend data validation. Advanced Python Proficiency: Expert-level skills in Python for building custom test scripts and working within AI/ML ecosystems. AI/ML Validation Experience: Proven experience testing model outputs using diverse metrics (e.g., Semantic Similarity, NLP metrics, an

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. We’re looking for a Field Application Engineer who’s wired for AI/ML, fluent in real-world problem-solving, and excited to build with the people actually using what we make. You will collaborate closely with the sales team and enterprise customers, leveraging your deep technical knowledge in AI to drive the adoption of our products and solutions. This is a customer-facing role that requires both technical expertise and excellent communication skills to convey complex technical concepts to non-technical stakeholders. This role is remote based out of North America with preference near one of our main hubs Santa Clara, CA; Boston, MA; or Toronto,ON. 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 You’ve lived in the AI/ML trenches, whether as a field engineer, a solutions architect, or the one tapped in when things needed to “just work.” You speak both machine and human. Whether it’s a researcher or a skeptical executive, you know how to break things down and bring them to life. You’re fired up about generative models, LLMs, and the edge of what’s possible when software meets purpose-built silicon. Work directly with customers in mee

The Data Engineering team’s mission is to ensure high-quality data to enable data-informed decision-making across Asana. You will build data artifacts that are leveraged by Product and Business Data Science teams to optimize our user adoption, growth, and experience. In this role, you will partner with the Infrastructure team to build a self-service analytics platform for the company. This role is based in our Vancouver office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday; most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Design, implement, and scale end-to-end data products that support growing data processing and analytical needs Transform raw data into actionable insights to drive product strategy and power in-depth analyses and reporting Leverage AI to build self-serve tools and accelerate Data/GTM workflows Partner with data scientists, domain experts, and engineering teams to develop a roadmap that aligns with our business goals Implement systems that guarantee data quality, governance, and availability About you 5+ years of experience in Data Engineering or Software Engineering Experience in data modeling and building scalable data pipelines involving complex transformations Proficiency in data processing and storage technologies like Databricks, AWS/S3, Python/Scala/Java, SQL, Spark, and Airflow Proactive and innovative in identifying and addressing performance bottlenecks in existing workflows Motivated to work closely with cross-functional partners to evolve our analytical data model Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making At Asana, we're com