Forward Deployed Engineer, Inference

• Embed directly with customer engineering teams to architect the "connective tissue" between our AI models and their live, complex production environments.
• Design advanced model serving topologies, implementing multi-tenant architectures, intelligent model routing, and cross-datacenter failover strategies for multi-cluster environments.
• Optimize "AI-in-a-box" and private deployments, balancing localized SRE constraints like Kubernetes multi-cluster scale with raw model performance.
• Conduct rigorous benchmarking and profiling of customer LLM workloads, root-causing performance degradation (e.g., slow generation) via metrics, dashboards, and distributed logs.
• Accelerate hardware validation, collaborating with clients to run and support Cohere models on next-generation accelerators (GPUs, TPUs, AMD, and custom ASICs).
• Translate complex field friction into platform upgrades, delivering prescriptive feedback and contributing directly back to core product features.
• Ensure Day-1 production reliability, assisting customers in establishing sound deployment patterns, SLOs, and observability frameworks.

:

• 8+ years of engineering experience running production infrastructure, designing large-scale distributed systems, or deploying enterprise software in complex environments.
• Deep technical depth in production Kubernetes, including orchestration across multi-cluster and hybrid/multi-cloud ecosystems (GCP, Azure, AWS, OCI).
• Strong understanding of LLM architecture and inference dynamics, specifically how attention mechanisms, compute-bound prefill, and memory-bound decode phases dictate live performance.
• Hands-on experience with modern inference engines and optimization stacks (e.g., vLLM, TensorRT-LLM, lmd, or Dynamo).
• Familiarity with distributed serving techniques, such as prefill/decode disaggregated serving, distributed KV caching, and multi-GPU workloads.
• Exceptional customer-facing technical leadership, with a proven track record of scoping highly ambiguous problems and steering executive technical stakeholders.
• The high agency, grit, and adaptability to write same-day production code while managing client-side deployment politics or blockers.
• Strong programming foundations in Python, Go, or C++, comfortable moving fluidly between backend data pipelines and infrastructure layer tuning.

• A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.

• Full health and dental benefits, including a separate budget for mental health.

• RRSP matching, 401K, Pension Scheme.

• 100% Parental Leave top-up for up to 6 months, for either parent.

• Annual enrichment benefits:

Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching.

• 6 weeks of paid vacation (30 working days!)

• Budget for traveling to other offices if you are remote, plus an annual company offsite.

• Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon.

• For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.

• For those not near an office: a co-working benefit so you can work alongside others in your city.

• Everyone receives a $500 home office stipend to set up your workspace properly.

If any of the above doesn't line up exactly with your experience, we still encourage you to apply.

We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form , and we will work together to meet your needs.

We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.

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