Forward Deployed Engineer, Inference

Cohere; United States; Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Lunch stipend

Health and dental benefits

RRSP matching / 401K

Parental leave top-up

Enrichment benefits

Education stipend

6 weeks paid vacation

Travel budget to other offices

Home office stipend

Job summary

Cohere is seeking a Staff Forward Deployed Engineer to bridge frontier AI capability with complex customer environments. You will own the architecture for ambiguous inference challenges—from multi-tenant model serving to cross-datacenter disaster recovery and custom hardware validation—ensuring latency, throughput, and resilience in the field.

You will embed with customer teams, lead technical adoption end-to-end, and translate field friction into platform improvements, while working with

Qualifications

• 8+ years engineering production infrastructure experience in large-scale environments.
• Strong Kubernetes expertise across multi-cluster and multi-cloud setups (GCP, Azure, AWS, OCI).
• Deep understanding of LLM architecture, inference dynamics and live performance.
• Hands-on with modern inference engines and optimization stacks.

Responsibilities

• Embed with customer teams to connect AI models to production environments.
• Design topologies for multi-tenant serving and cross-datacenter failover.
• Optimize private deployments balancing SRE constraints and model performance.
• Benchmark and profile customer LLM workloads, diagnose slow generation.
• Support Cohere models on GPUs, TPUs, and custom accelerators.
• Translate field feedback into platform improvements and product features.
• Ensure Day-1 production reliability with clear deployment patterns and observability.

Skills

Kubernetes

LLM inference

Python

Go

C++

Multi-cluster

Distributed systems

Customer leadership

Cloud platforms

Performance optimization

Tools

vLLM

TensorRT-LLM

lmd

Dynamo

Job description

Who are we?

Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.

We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.

We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.

We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!

Why this role?

Are you energized by bridging the gap between frontier AI capability and complex customer reality? Do you want to architect high-performance, resilient machine learning systems directly inside strategic enterprise environments? We are looking for a Staff Forward Deployed Engineer (FDE) to join our team. The team is responsible for taking our large language models and making them work reliably, securely, and at peak performance within our customers' custom infrastructure and data perimeters.

In this role, you will act as the principal technical translation layer between our core engineering teams and our strategic partners. You will own the architecture for highly ambiguous, customer-specific inference challenges—ranging from multi-tenant model serving to multi-datacenter disaster recovery and custom hardware validation. You will lead technical adoption end-to-end, ensuring our models achieve exceptionally low latency, high throughput, and seamless resilience in the field.

As a Forward Deployed Engineer, you will:

• 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.

You may be a good fit if you have:

• 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.

Full-Time Employees at Cohere enjoy these Perks:

• 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.

How and Where We Work:

• 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 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.