Join the Context Engine team to build the knowledge layer agents use with Elasticsearch. The role involves writing production TypeScript/Python code, designing telemetry and evaluation strategies, iterating on prompts, skills and automations safely in production, and partnering with data scientists, backend engineers and product. Requires 10+ years of software engineering experience and experience shipping AI-driven products on production traffic.

Cast AI is hiring a Senior Software Engineer for the Kimchi Harness team to design and implement harnesses that enable model planning, execution and evaluation. Responsibilities include architecting planner/executor/evaluator pipelines, managing agent memory and context, owning harness surface integrations (TUI, MCP, telemetry), and shipping end-to-end features. Strong production experience with Go or TypeScript, systems programming, database performance tuning, cloud (AWS/GCP/Azure) and Kubernetes, and observability/CI-CD practices are highlighted. Role is remote-first across listed Eastern European countries; the posting states Cast AI does not provide visa sponsorship. Salary range listed: €6,500–€9,000 gross.

Join Kraken's Agent Systems team to design, prototype, and productionize AI-powered agent systems that integrate with internal APIs and data sources to automate workflows. Requires 5+ years building production software with strong backend fundamentals (APIs, distributed systems, data modeling, reliability), hands-on experience with AI/ML or LLMs and inference pipelines, and comfort working fullstack in ambiguous 0→1 environments. Responsibilities include architecting inference pipelines, ensuring safe/observable agent execution, and collaborating across product, infrastructure, and operations.

Owner of the technical layer for Kraken's internal AI platform: build and operate the governed integration gateway, onboard connectors and authentication flows, implement tiered spend and data controls, build internal tooling (agent scaffolding, prompt assets, evaluation harnesses), run enablement and documentation, and administer enterprise AI platform operations including vendor and provisioning management.

Lead technical direction for the Duo Agent Platform, build reliable orchestration for agents and flows (session lifecycle, tool invocation, concurrency, retries, timeouts), ensure support across GitLab.com, Dedicated, and Self-Managed (including self-hosted models), define evaluation and benchmarking practices, and design governance/safety controls. Role is hands-on, involves cross-team alignment, mentoring, and participating in incident on-call. Requires 8+ years software engineering experience with hands-on LLM/agent experience. Remote in Canada, Poland, United Kingdom, and United States (locations listed in posting).

Join GitLab's Trusted Agentic Development team to own the architecture and prototypes that close the validation gap for AI agent–authored code. Design mid-loop feedback, build language-aware validation approaches (starting with Rust, Ruby, and Go), collaborate across teams, and measure adoption and trust in an all-remote environment. Poland base salary range provided.

Lead inference strategy and technical collaborations with AI labs and enterprises across EMEA. Drive scalable production deployments and optimizations for LLM/VLM inference (latency, cost per token, memory, networking). Architect high-performance inference pipelines using NVIDIA stack (Dynamo, TensorRT-LLM, NIM), vLLM, SGLang and other backends, and translate deployment insights into product feedback. Requires MS/PhD or equivalent and 8+ years in AI/ML infrastructure.

Role focuses on enhancing Elasticsearch's vector similarity search (design, implement, and fix features), contributing to Lucene where relevant, working with a globally distributed engineering team, and writing idiomatic modern Java. Requires professional experience with vector similarity/vector databases (experience with HNSW, IVF, or similar), strong core Java skills, familiarity with data storage technologies, and experience collaborating on open source and distributed teams.

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.

NVIDIA is hiring a Senior Deep Learning Software Engineer for inference: design, build, and optimize GPU-accelerated software and inference frameworks (vLLM, SGLang) for LLMs and generative/multimodal models. Requires Masters/PhD or equivalent, 5+ years software development, strong C/C++ and software design skills; CUDA, NCCL, CUTLASS, Triton, performance optimization, and production inference experience are listed as relevant. Poland base salary ranges provided: 221,250–383,500 PLN (Level 3) and 292,500–507,000 PLN (Level 4).

Join the Growth Foundations Group to build and ship agent orchestrations, automated workflows, and system integrations that power paid growth, lifecycle, organic, CRO, incentives, referrals, and creative pipelines. The role requires 3+ years building automation workflows or agentic systems, strong API integration skills, experience with LLM APIs and prompt engineering, and domain familiarity with growth/marketing.

Work on the Duo Agent Platform in the GitLab monolith (primarily Ruby) and occasionally the AI Gateway (Python). Responsibilities include designing and implementing GraphQL/REST APIs, developing backend features, improving automated tests (RSpec), troubleshooting production issues (Tier 2 on-call), and collaborating with product, UX, frontend and AI teams to ship scalable, secure AI-enabled backend functionality.

You will author merged PRs and build integrations (libraries, agent frameworks, MCP servers, automation platform connectors) so developers and AI agents can access SearchApi. Required: proven merged open-source contributions in repos you don't own, fluency with Ruby/Python/TypeScript and at least one agent/automation framework, and strong written English for docs and PRs.

NVIDIA seeks an engineering manager to lead engineering activities for productizing deep learning models, including creating, optimizing, and deploying training and inference workloads. Role requires strong algorithms/DL background, programming, debugging, performance analysis, and 8+ years' experience (including 3+ years management). Position is based in Poland (remote/Warsaw) with travel to conferences/sites occasionally. Poland salary ranges are provided.

Senior engineer responsible for owning GPU/accelerator clusters and related stack (drivers, runtimes, device plugins, node config, schedulers, serving frameworks) to enable in-house model training and inference. Requires 5+ years in infrastructure engineering with hands-on experience operating GPU or accelerator-backed production environments, strong systems fundamentals (Linux, networking, storage, containers, Kubernetes), Python proficiency, and experience with ML serving frameworks and observability.

Join NVIDIA to architect and implement high-performance inference stacks for large models: optimize GPU kernels and compilers, extend inference frameworks (vLLM), define benchmarking (MLPerf), and scale multi-GPU/multi-node deployments. Requires strong Python and C/C++ skills, GPU programming (CUDA, NCCL), experience with containers and orchestration, and 5+–7+ years of relevant experience depending on degree.

Remote senior-level Data Scientist position requiring 7+ years of experience to lead complex projects end-to-end, including ML deployment, NLP/LLM development, Bayesian campaign analysis, experiment design, and work with production data pipelines and columnar databases. Role emphasizes privacy-first data practices and occasional travel (~2x/year).

Join NVIDIA's AI networking acceleration team to develop a highly optimized, low-level inference framework that leverages GPU kernels, RDMA network cards, and hardware offloads. The role requires strong systems knowledge (computer architecture, operating systems, TCP/IP) and extensive experience in modern C++/C/Rust and Linux environments.

Join a multidisciplinary team to design, develop, and optimize high-performance CPU and GPU-accelerated software libraries used in AI, data analytics, image processing, computer vision, and scientific simulation. Role requires developing scalable library software, performance tuning and benchmarking across architectures, collaborating with internal and external partners, and providing technical leadership. Preferred: MSc/PhD or equivalent experience and 5+ years developing and optimizing parallel numerical applications with GPU acceleration (CUDA).