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You will leverage modern AI-assisted development practices and tooling to accelerate delivery while maintaining high code quality.
You will use AI in your daily coding and advocate to the team and customers an evolving state-of-the-art of how best to do this.
You will demonstrate resiliency to experiment and try multiple AI approaches that may not work — because no one has tried them before.
You will provide mentorship and coaching to engineers in, and beyond, your team.
You will contribute positively to a culture where everyone can bring their full and authentic self and where we do our best work as a result.
You will build AI-powered product features using technologies such as large language models (LLMs), vector stores, and agentic workflows to improve security signal analysis and customer outcomes.
You continuously improve engineering efficiency by leveraging AI tooling, automation, and documentation to streamline development and operational workflows.
You will own medium-to-large features end-to-end, including design, implementation, deployment, monitoring, and iteration in production environments.
You will work across full stack solutions that span from user experience through to backend data and service layers
You will develop software using languages such as TypeScript, JavaScript, React, and others
You will design, develop, and maintain backend services and APIs that support agentic workflows and platform capabilities
You will collaborate closely with PM, Design, and partner teams to design and develop scalable solutions
You will respond, resolve, and integrate customer feedback with agility and dedication
You lead by example, adhering to best engineering practices, raising the quality bar, and improving the team's response to customer incidents
With minimal supervision, tests and explores various design options for a product/solution feature, outlining strengths and weaknesses of each option.
You leverage appropriate AI tools and practices across the software development lifecycle (SDLC) in a disciplined manner.
You understand and apply security best practices and establishes code invariants to model security as code, ensuring each layer is independently secure, and minimizing risk with minimal supervision.
You will apply Security-by-Design and Responsible AI principles when building features that leverage AI to enhance threat detection and response capabilities.
You contribute positively to team culture, demonstrating growth mindset, openness to feedback, and a collaborative approach in a fast-paced, data-driven environment.
Requirements
Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Hands-on experience of building and operating LLM powered agentic systems in production, with direct ownership over quality, reliability, and iterations
4+ years of experience building production software using one or more modern programming languages such as AI LLM, agents, skills, C#, Java or Python.
Demonstrated proficiency with AI-assisted software development tools and workflows (e.g. AI coding agents, LLM-powered development environments)
Expertise in LLM and GenAI Application development.
GitHub Copilot and Copilot Workspace — AI pair programming, CLI, and task-oriented development
Prior experience using agentic plugins, agents, skills, hooks, etc.
Prior experience building with Agent SDKs, large language models (LLMs), prompt engineering, or AI orchestration frameworks).
Familiarity with agentic AI development patterns — multi-step reasoning, tool/function calling, retrieval-augmented generation (RAG), and human-in-the-loop workflows.
Strong product mindset with a track record of owning ambiguous problem spaces and driving them to high-quality outcomes
Solid engineering fundamentals, including systems design, performance, and debugging in complex production environments
Track record of designing, running, and optimizing evaluations for agentic systems, including tools, prompts, and agent loops
Strong understanding of Generative AI & software engineering fundamentals, data structures, and problem-solving.
Ability to learn new technologies quickly and adapt to deliver customer and business impact.
Nice to have
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
4+ years of experience in cloud services or AI systems. Experience building and shipping AI features for world-class production systems.
Excellent communication skills and ability to collaborate within a multi-disciplinary team.
Proven experience as a Software Engineer delivering large-scale, production-quality systems.
Proficient software engineering fundamentals: system design, algorithms, testing, debugging, and code review.
Demonstrated ability to lead technical direction and mentor peers in a collaborative team environment.
Comfort working in ambiguous, fast-moving problem spaces where best practices are still being established.- Hands-on experience with AI-powered developer tooling and coding assistants, such as:
Experience dogfooding, evaluating, and forming opinions on emerging AI developer tools, and translating those insights into team-wide best practices.
Experience designing and building RESTful APIs or GraphQL services.
Track record of high development velocity through effective use of AI coding assistants and automation
Experience with database technologies (SQL, NoSQL)