Senior AI/ML Engineer

• Design and build AI-powered features — LLM agents, retrieval, and event intelligence — that operate on high-volume, real-time event streams, from problem framing through production deployment and monitoring.
• Architect and own the systems behind them: agent and prompt orchestration, retrieval pipelines, tool/API integrations, and low-latency inference and evaluation at scale.
• Reason about consistency, throughput, fault tolerance, and cost across services that must stay reliable under bursty, unpredictable load.
• Take AI features from prototype to production, establishing the evaluation, guardrail, observability, and improvement loops that keep them accurate and trustworthy over time.
• Partner with platform, product, and applied-research teams to define what “good” looks like and to integrate AI cleanly into existing services.
• Raise the bar through example, reviews and mentorship, and help shape the team’s technical direction.

What you’ll bring

• 5+ years of software engineering experience, with meaningful time spent building and operating production distributed systems (high-throughput services, streaming/event-driven architectures, or large-scale data platforms).
• Hands-on experience building and shipping AI systems in production — LLM-powered applications, agents, or retrieval — including the surrounding orchestration, serving, and evaluation, not just prototypes.
• Strong programming fundamentals and comfort moving between systems and AI/application code.
• Solid grounding in applied AI fundamentals: prompting, retrieval, agent patterns, and how to evaluate and guardrail LLM behavior.
• Experience with cloud infrastructure (AWS, GCP, or Azure), containers, and orchestration (Kubernetes).
• A pragmatic, reliability-minded mindset: you optimize for systems that work correctly at scale, and you can articulate the trade-offs behind your choices.
• Strong communication and collaboration skills, and a track record of raising the quality of the teams and systems around you.

Nice to have

• Experience with LLMOps tooling and patterns — evaluation harnesses, prompt/version management, tracing and observability for agents, and online/offline eval consistency.
• Deep experience serving LLM-based systems in production, including retrieval-augmented generation, multi-step agents, and tool use.
• Background in anomaly detection, event correlation, or applied problems in observability, AIOps, or reliability.
• Familiarity with the ecosystem — e.g. LLM APIs and frameworks such as LangChain or LlamaIndex, vector databases, and distributed data/compute tools such as Kafka, Airflow, or Spark.
• Contributions to open-source AI or distributed-systems projects.

What we offer

As a global organization, our total rewards approach is competitive with industry standards and aligned with local laws and regulations. Learn more, including country-specific offerings, on our benefits site.

Your package may include:

• Competitive salary
• Comprehensive benefits package 
• Flexible work arrangements
• Company equity*
• ESPP (Employee Stock Purchase Program)*
• Retirement or pension plan*
• Generous paid vacation time
• Paid holidays and sick leave
• Dutonian Wellness Days & HibernationDuty - companywide paid days off in addition to PTO
• Paid parental leave: 22 weeks for pregnant parent, 12 weeks for non-pregnant parent (some countries have longer leave standards and we comply with local laws)*
• Paid volunteer time off: 20 hours per year
• Company-wide hack weeks
• Mental wellness programs

*Eligibility may vary by role, region, and tenure

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