Join GitHub's Copilot Agents organization to design, implement, and operate systems that enable AI agents to acquire, retain, and apply software-development context (agent memory, context retrieval, search, knowledge graphs). Role involves end-to-end platform and API development, defining technical direction, establishing evaluation and telemetry, ensuring privacy/security, participating in on-call rotations, and mentoring engineers. Requires substantial production software engineering experience and familiarity with languages such as Rust, Go, Python, TypeScript, or similar.

Lead role requiring 12+ years of full‑stack engineering experience to design, build, and own end‑to‑end features (UI, APIs, backend, data models) and Salesforce components (LWC, Apex, SOQL). Use AI‑assisted coding tools (Cursor, Claude Code, Codex, Copilot), implement integrations (REST, event‑driven, MuleSoft), contribute to CI/CD and automated testing, and provide production support.

Join GitLab's Duo Client SDK team to design and implement versioned TypeScript packages and SDK clients used by editor extensions and web Duo Chat. Work includes Node.js core design, API and semantic versioning, package extraction and publishing, Vue 3 client work, credential handling, bundle optimization, testing, and on-call support. Remote role for Canada and the United States.

Lead design and implementation of Zip’s enterprise Data & AI Platform to support analytics, machine learning, Generative AI and Agentic AI. Responsibilities include building scalable batch and real-time pipelines, vector search and RAG capabilities, lakehouse/open table formats, governance, observability, and mentoring engineers. Requires 8+ years' experience and deep expertise with cloud data platforms and tools (SQL, Python, dbt, Airflow/Dagster, Kafka/Spark). Salary range listed: $134,000–$168,000/year. Visa sponsorship is not available.

Own your function's AI strategy and prioritize high-impact opportunities; prototype and configure AI agents (no-code/low-code), manage agent operations and metrics, build a Champion network, and drive adoption and change management while partnering with the Enterprise AI engineering team. US base salary range listed: $203,200–$345,600 USD (annual).

Role to design and develop algorithms and models for price and promotion optimization using optimization and deep learning techniques. Responsibilities include solution development, presenting results to technical and non-technical stakeholders, cross-functional collaboration, and building reusable analytics artifacts. Minimum 3 years' experience; preferred experience with Gurobi, forecasting, predictive modeling, and a quantitative degree (PhD preferred).

Join GitLab's Agent Foundations stage to develop, ship and maintain backend features (primarily in Python) for the Duo Agent Platform, Duo Workflow Service and AI Gateway. Work with LangChain/LangGraph and design/implement APIs (GraphQL/REST), improve automated tests (pytest), troubleshoot production issues on on-call rotations, and collaborate async across cross-functional teams. Role is remote and open to candidates in Canada, Poland, and the United Kingdom.

Mid-level Software Engineer (Software Engineer II) responsible for designing, developing, testing, and maintaining cloud-based software. Requires 3+ years' experience, strong C#/.NET and API skills, familiarity with Docker, CI/CD, Azure/AWS, and experience with AI development tools. Works cross-functionally on product and platform initiatives. Remote within the US.

Hands-on senior engineering role building GitHub Copilot Code Review: define and implement how the review agent reasons and which models run, own reliability and on-call for a high-throughput service, design offline and online evaluations, collaborate with research and model teams, and mentor senior staff. Requires extensive software engineering experience and working with models at scale.

Role to design MLIR dialects and APIs, implement compiler optimizations and kernel generation for neural networks, and collaborate with framework and hardware teams. Requires a BS/MS/PhD or equivalent, 3+ years' relevant experience in performance analysis and compiler optimizations, experience with MLIR/XLA/LLVM, strong C++ and Python skills, and familiarity with GPU programming (CUDA/OpenCL) and deep learning frameworks (PyTorch/JAX). Salary ranges provided for levels 3 and 4.

CrowdStrike seeks a Senior Machine Learning Engineer to support an AIDR engineering team focused on LLM post-training, scalable low-latency inference, and data engineering for customer-facing AI applications. Responsibilities include building and maintaining data pipelines, supporting model training and inference at scale (including GPU clusters), collaborating with data scientists and engineering teams, and following engineering best practices. Location: USA - Remote. Posted U.S. base salary range: $140,000–$215,000 per year.

CrowdStrike is hiring a Data Scientist to lead R&D and production deployment of LLMs and GenAI agents for cybersecurity. Responsibilities include end-to-end research (data sourcing, labeling, modeling, evaluation), technical leadership, mentoring, and collaborating with engineering and product teams. Requires an advanced degree (MS/PhD), 5+ years of applied ML/research experience, strong Python and deep learning framework skills, GPU optimization knowledge, and experience with LLM training or deployment at scale. US base salary range: $120,000–$180,000 per year.

NVIDIA is hiring an AI Compiler Engineer to work on kernel generation, computational graph optimizations, and compiler frameworks for next-generation GPUs. The role requires 3+ years of relevant industry compiler experience, hands-on MLIR knowledge, and strong C/C++ and Python programming and software design abilities. Collaboration with hardware, software, and research teams and experience with AI workloads (inference/training, LLMs, datacenter deployments) are emphasized.

Senior AI Builder role requiring 6+ years software development experience (>=3 years building ML models). Responsibilities include solution architecture, integrating AI models with legacy systems (e.g., CRM, core wallet, SAP), driving CI/CD and MLOps practices, applying security-by-design and data privacy controls, and leading cross-functional teams using AI-assisted development tools (e.g., GitHub Copilot). Strong cloud (AWS/Azure/GCP), containerization (Docker/Kubernetes), microservices, APIs, Agile/DevOps and LLM/prompt-engineering expertise expected.

The Director, AI Governance & Enterprise Solutions is the senior AI technical lead responsible for the Momentive Context Library, defining and enforcing technical standards for AI agents, leading agent review and approval, building agents and tooling for the AI Operations Hub, and advising spoke teams on architecture, deployment, monitoring, and security. Requires 7+ years in software/AI systems with at least 3 years working with LLMs, agent architectures, and production AI deployments.

The role leads enterprise MarTech architecture and platform engineering to deliver AI-ready marketing technology solutions, including designing intelligent agents for campaign workflows, driving integrations and migrations (CMS, webinar tools, etc.), creating technology roadmaps, and establishing standards and governance. Requires 10+ years in marketing technology/solutions architecture and 5+ years designing AI/ML or intelligent automation systems.

Lead end-to-end product and engineering efforts to improve Copilot code review quality, context, memory, and evaluation infrastructure. Responsibilities include designing evals and metrics, making quality/latency/cost tradeoffs, shaping experiences across VS Code/Copilot app/CLI, and keeping distributed services healthy (including on-call).

Lead and grow multiple engineering teams building Agentic AI systems, orchestration frameworks, and guardrail systems for compliance and customer support. Set technical vision and roadmaps, drive architecture and delivery of production LLM-based systems, and partner with Compliance, Operations, and Product leadership. Requires 10+ years in software engineering, 5+ years engineering management (2+ managing managers), and proven experience shipping LLM/Agentic AI applications to production.

Technical leader responsible for architecting and driving implementation of large-scale, low-latency distributed inference systems and full model lifecycle management. Requires deep expertise in GPU architecture and low-level performance tuning (CUDA, kernels), cloud-native multi-tenant model serving, orchestration (Kubernetes, Ray), and open source ecosystem engagement. Minimum 16+ years technical experience and significant leadership experience (7–10+ years cited).

Develop and maintain coding-intensive training (Java, REST APIs) and lab environments focused on agentic AI topics—tool/function calling, RAG, prompt engineering, context management, and orchestration. Role requires hands-on experience building AI agents (e.g., LangChain, LangGraph, Claude Agent SDK), 3+ years creating technical training/curriculum, and familiarity with Git and API tooling.