Ai Developer Jobs

CAPCO POLAND * We are looking for Poland based candidate. At Capco Poland, we’re not just another consultancy - we’re the spark behind digital transformation in the financial world. As a global leader in technology and management consulting, we thrive on helping clients tackle the toughest challenges across banking, payments, capital markets, wealth, and asset management. THE ROLE The engagement combines strong Cloud and Platform Engineering expertise with a solid understanding of Generative AI technologies and a consulting mindset. You will collaborate with architects, engineering teams and business stakeholders to define integration approaches, facilitate architectural alignment and translate technical concepts into implementable solutions. We are looking for someone comfortable operating at the intersection of solution architecture and hands-on engineering – discussing how enterprise applications and platforms should integrate, recommending appropriate technical approaches and contributing to their implementation. SCOPE OF COOPERATION Designing and implementing cloud and platform solutions based on AWS and/or Azure Building and evolving cloud infrastructure using Terraform / Infrastructure as Code Contributing to the architecture and implementation of solutions leveraging Generative AI and LLM technologies Designing integrations between cloud/AI platforms and enterprise technologies such as Grafana, Collibra, Splunk, Kubernetes, LeanIX, Envoy and LiteLLM Collaborating with client architects and engineering teams to define integration patterns, interfaces and technical solutions Facilitating architectural alignment across multiple teams and stakeholders Translating business and technical requirements into scalable solution designs Combining architectural thinking with practical, hands-on implementation Identifying technical dependencies, risks and trade-offs and communicating them clearly to stakeholders Working within an Ag

We are now looking for an AI Developer Technology Engineer Interns. Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time — the era of AI has begun. Image recognition and speech recognition — GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. The GPU started out as the engine for simulating human creativity, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human creativity and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for Deep Learning, and NVIDIA is increasingly known as “the AI computing company.” Come join a team full of world-class computer scientists to work in its Compute Developer Technology team as an AI Developer Technology Engineer. What you will be doing: Work and develop state of the art techniques in LLM/AIGX/GR, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures You will provide the best AI solutions using GPUs working directly with key customers Collaborate closely with the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a rock star leader for our AI DevEx team. This team plays a crucial part in transforming how the Snowflake product is developed, evaluated and supported. The job is no less than building the ecosystem that powers our AI-pilled engineers and our agentic organizations and reinvents the SDLC for Snowflake. As the manager for this growing team, you will lead the group of engineers working to reinvent how code is written, reviewed and runs in production to usher scale and velocity for the AI era. With context as the new source code, you will make it possible for every engineer at Snowflake to deliver through intent and direction. In this role, you will: Lead, coach, and grow the ES AI DevEx team while creating a high-energy, cohesive environment with strong planning, ownership, and career development. Deliver the vision and roadmap for transforming the SDLC for all Snowflake engineers. Drive measurable improvements in code review latency, ensure Snowflake developers can use the latest harnesses and models, and create the golden paths that agentic codebases are built upon. Act as an agent of clarity in a space that is moving fast, making high quality decisions quickly by keeping up with the latest developments in the industry. Own operational excellence for the area

The NVIDIA PerfTech team is looking for a talented C++ Software Engineer to help build the next generation of AI-powered developer tools. You will apply strong C++ and software-engineering fundamentals while gaining hands-on experience with agentic workflows, retrieval systems, and AI services. In this role, you will contribute to Genie, NVIDIA’s company-wide AI knowledge and developer-productivity service. You will work across C++ tools and AI services to help engineers find information, understand complex systems, and work more effectively. What You’ll Be Doing: Develop production-quality C++ components, APIs, and integrations for NVIDIA’s AI-powered developer-tools ecosystem. Build capabilities connecting native C++ tools with Genie’s retrieval and agentic features. Contribute to agentic workflows, retrieval systems, ingestion pipelines, MCP tools, APIs, and enterprise integrations. Build benchmarks and improve retrieval quality, reliability, performance, and resource usage. Own features from investigation and design through implementation, testing, and delivery. Collaborate with graphics, software, and hardware teams developing performance-analysis and developer tools. What We Need to See: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience. 5+ years of modern C++ programming skills gained through professional experience, internships, or substantial technical projects. Good understanding of data structures, algorithms, object-oriented design, multithreading, debugging, and testing. Ability and motivation to work across C++ systems and Python-based AI services. Familiarity with AI-powered applications, agentic workflows, retrieval systems, or related technologies. Abil

Job Overview: We are looking for a Senior GenAI Developer to design, build, and productionize agentic AI systems—LLM-powered agents that can plan, use tools, orchestrate workflows, and operate reliably under enterprise constraints. You will own key parts of the agent architecture (planning, tool use, memory, evaluation, safety/guardrails, and observability) and deliver end-to-end solutions across RAG, function/tool calling, multi-agent coordination, and scalable deployment. Key Responsibilities Design and implement agentic systems: single-agent and multi-agent architectures (planner/executor, supervisor-worker, routing, reflection, critique, task decomposition). Build robust tool-using agents: function calling, tool schemas, tool authorization, retries, rate limiting, and sandboxing. Implement RAG + memory patterns: retrieval strategies, hybrid search, context assembly, long-term memory, and grounding/citation behaviors. Develop workflow orchestration for agent execution (state machines/graphs), concurrency controls, and deterministic execution where possible. Productionize GenAI services: APIs, background jobs, streaming responses, caching, and cost/latency optimization. Establish agent evaluation: golden sets, simulation-based evals, LLM-as-judge with mitigations, task success metrics, regression testing. Build observability and safety: tracing, token/tool telemetry, anomaly detection, prompt injection defenses, data leakage prevention, policy enforcement. Collaborate with product, security, and platform teams to deliver enterprise-ready solutions and integrate with internal systems (data, identity, workflow). Mentor engineers, set coding standards, and contribute to architecture reviews and technical roadmaps. Required Qualifications 6+ years software engineering experience; 2+ years building LLM/GenAI systems in production. Strong programming skills in Python (required) and/or TypeScript/Node.js. H

Intern, AI Developer/ Stagiaire en développement IA — QC, CAN. Apply via Workday.

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 Baseten's engineers want to work in an AI-first way. What's missing isn't enthusiasm — it's the platform underneath it. Today everyone assembles their own agent config, context files, and MCP servers, so the good patterns stay trapped in individual setups instead of becoming defaults everyone inherits. You'll build that platform: the agent configurations tuned to our monorepo, the context and tooling layer that makes agents competent in our codebase, the evals that tell us which approaches actually work, and the rollout mechanics that get a new engineer productive with agents in week one. You are not here to mandate how engineers use AI — you're here to make the good path the easy path. Success looks like teams adopting what you build because it beats what they'd cobble together themselves, not because a policy requires it. Platform engineer, not AI evangelist. Ship infrastructure, measure it, kill what doesn't work, let adoption be the referee. The playbook for AI-first SDLC doesn't exist at any company yet. You'll write ours. WHAT YOU'LL BUILD Agent substrate — Repo-level context infrastructure that makes agents competent in our codebase ( CLAUDE.md/AGENTS.md conventions, architecture and domain context, and the tooling to keep it accurate as code moves). Internal MCP servers giving agents scoped access to CI, observability, incident tooling, deployment state, and docs. Shared skills, subagents, and hooks th

We’re looking for a Staff Software Engineer to integrate and improve our AI developer experience so that engineers at Asana can use AI to increase their velocity. As part of the AI Developer Productivity team, you’ll set technical direction and build the next generation of AI-powered developer tools across editors, IDEs, CLIs, code review, and cloud and local coding agents. This role is based in our New York City 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 and build AI-augmented workflows and systems that help coding agents understand the codebase, follow engineering practices, and enable Asana engineers to complete software development tasks faster and with more confidence. Design and scale autonomous cloud agents that take on complex, multi-step engineering tasks to reduce toil and enable engineers to focus on higher-leverage work. Build and refine IDE, editor, and CLI integrations that make AI-assisted development feel intuitive in engineers' daily work. Create reusable agent skills, tools, context, and integrations that teams across Asana can build on rather than reinvent. Improve AI-assisted code review workflows so engineers get faster, higher-quality feedback before and during review. Drive adoption of AI developer tools across engineering through usability improvements, measurement, documentation, and enablement. Set technical direction for the team, balancing experimentation with reliability, maintainability, and long-term platform thinking. Partner cross-functionally with teams across the engineering organization to understand engineering needs, identify workflow friction, and scale high-impact solutions

About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Location: Austin, TX | New York, NY | San Francisco, CA (metro areas) About Cloudflare At Cloudflare, our mission is bold yet simple: to help build a better Internet. Our global network handles trillions of requests each month, protecting and accelerating applications without added hardware, software, or code changes. Our Developer Platform, including Workers, Workers AI, R2, KV, Durable Objects, and Pages, empowers developers to build and

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the Role This isn’t a typical engineering role. You won’t be embedded in a single product team or siloed in one product area. Instead, you’ll sit within Platform Engineering, own the AI-assisted coding domain, and work across all of engineering at Sentry, focused specifically on how AI coding agents participate in our software development lifecycle. For AI coding agents to work well in our repo, the internal systems they depend on need to be accessible via API, not locked behind UIs that require human interaction. Right now, many of those systems aren’t agent-ready. You’ll audit and prioritize that gap, expose those systems programmatically, and build the connections that let tools like Claude Code operate on them end-to-end. From there, the scope expands to improving the quality of AI-generated pull requests and automating the engineering work that’s important but consistently deprioritized. You will look from context engineering standpoint to see what to send to our model; you will look from harness engineering standpoint to see the tools it can use, the permissions it has, the state it carries forward, the tests it has to pass, the logs you capture, the retries, checkpoints, guardrails, and evals. You’ll work closely with the dev infrastructure team as your home base, then collaborate across every product team coding in our repo once the tooling foundation is in place. It’s a broad role with real impact, and the work you do will directly change how Sentry engineers ship software. What You’ll Do Audit Sentry’s internal developer systems and make them API-ready for AI agents. You’ll prioritize and drive the work of ex

We're looking for a Senior Software Engineer to integrate and improve our AI developer experience so that engineers at Asana can use AI to increase their velocity. As part of the AI Developer Productivity team, you'll build the next generation of AI-powered developer tools across editors, IDEs, CLIs, code review, and cloud and local coding agents.This role is based in our New York City 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 and build AI-augmented workflows and systems that help coding agents understand the codebase, follow engineering practices, and enable Asana engineers to complete software development tasks faster and with more confidence. Design and scale autonomous cloud agents that take on complex, multi-step engineering tasks to reduce toil and enable engineers to focus on higher-leverage work. Build and refine IDE, editor, and CLI integrations that make AI-assisted development feel intuitive in engineers' daily work. Create reusable agent skills, tools, context, and integrations that teams across Asana can build on rather than reinvent. Improve AI-assisted code review workflows so engineers get faster, higher-quality feedback before and during review. Drive adoption of AI developer tools across engineering through usability improvements, measurement, documentation, and enablement. About you 5+ years of working in large codebases Experience building developer tools, internal platforms, infrastructure, IDE/editor integrations, CLIs, or workflow automation. Hands-on experience with AI-assisted development tools (such as Cursor, Claude Code, or Codex), or extending coding agents, MCP-based int

We're looking for a Software Engineer to integrate and improve our AI developer experience so that engineers at Asana can use AI to increase their velocity. As part of the AI Developer Productivity team, you'll build the next generation of AI-powered developer tools across editors, IDEs, CLIs, code review, and cloud and local coding agents.This role is based in our New York City 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 and build AI-augmented workflows and systems that help coding agents understand the codebase, follow engineering practices, and enable Asana engineers to complete software development tasks faster and with more confidence. Design and scale autonomous cloud agents that take on complex, multi-step engineering tasks to reduce toil and enable engineers to focus on higher-leverage work. Build and refine IDE, editor, and CLI integrations that make AI-assisted development feel intuitive in engineers' daily work. Create reusable agent skills, tools, context, and integrations that teams across Asana can build on rather than reinvent. Improve AI-assisted code review workflows so engineers get faster, higher-quality feedback before and during review. Drive adoption of AI developer tools across engineering through usability improvements, measurement, documentation, and enablement. About you 3+ years of working in large codebases Experience building developer tools, internal platforms, infrastructure, IDE/editor integrations, CLIs, or workflow automation. Hands-on experience with AI-assisted development tools (such as Cursor, Claude Code, or Codex), or extending coding agents, MCP-based integratio

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. About the Role The AI Platform Engineering team is looking for a highly motivated and talented engineer who are passionate about continuous learning and excited to grow in a fast-paced, innovative environment. We are an agile team that operates iteratively, focused on building high-quality software and adhering to rigorous operational best practices across complex, cross-functional distributed systems. This full-time position reports to a Software Engineering Manager and can be located in our Bellevue, WA office, or you may work remotely from anywhere in the US where Smartsheet is a registered employer. What You'll Do Build the AI Platform Foundation : Lead the design and ownership of the core infrastructure that serves as the backbone for all Smartsheet AI experiences. Focus on building a robust, multi-tenant environment that reduces friction for internal teams, allowing them to deploy reliable and scalable AI features with ease. Standardize the AI Developer Path : Architect high-level abstractions and "Golden Path" APIs that democratize AI development across Smartsheet. By insulating product teams from infrastructure complexity, you will enable them to ship intelligent features with high velocity while guaranteeing safety and consistency at scale. Engineer AI Trust & Safety Systems : Establish the mission-critical monitoring and quality assurance layers that protect Smartsheet customers. By creating rigorous evaluation pipelines, you will ensure every AI-driven feature meets the high bar for safety, data privacy, a

We are seeking an experienced Senior Generative AI Developer to help drive the design, development, and integration of state-of-the-art Generative AI and agentic AI solutions across our enterprise Controls Technology platform. You will collaborate with cross-functional teams, contribute deep technical expertise in context engineering, retrieval systems, knowledge graphs, and multi-agent orchestration, and play a key role in delivering scalable, grounded AI solutions to enhance automation and operational efficiency. This role centers on architecting robust applications and agent systems on top of pre-trained and hosted foundation models — not on training or fine-tuning models. Key Responsibilities Collaborate with AI architects, leads, and stakeholders to design and implement generative and agentic AI solutions that address business challenges. Architect advanced context engineering strategies — context layering, chaining, compression, pruning/offloading, and memory management — to maximize reliability, provenance, and token efficiency in production. Design and implement advanced generative AI methods, including sophisticated prompt engineering and Retrieval-Augmented Generation (RAG) . Build and optimize RAG systems , including hybrid search, multi-vector retrieval, and re-ranking pipelines. Design and implement knowledge graphs and Graph RAG architectures to enable multi-hop reasoning, explainability, and traceable, grounded responses for high-value business domains. Architect agentic workflows and multi-agent systems using Google Agent Development Kit (ADK) and comparable frameworks (LangGraph, Microsoft Agent Framework, CrewAI), applying orchestration patterns such as supervisor/worker, hierarchical, and peer-to-peer. Design robust agent harnesses — governance, constraints, feedback loops, state/session management, and