Forward Deployed Engineer, Agentic Platform (West Coast)

ML Engineer · Senior · Full Time · Remote

San Francisco · RemoteUSD 180k – 280k2w ago
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Role

What you'll do.

Join Cohere's Forward Deployed Engineering team to architect and deploy enterprise-grade AI agents powered by frontier large language models. This role bridges Cohere's North AI workspace platform with enterprise customers across finance, healthcare, and telecommunications, requiring hands-on expertise in building production-grade LLM applications, RAG systems, and agentic workflows using Python and modern orchestration frameworks. You'll own the complete lifecycle from problem discovery through production deployment while working directly with Fortune 500 enterprises to solve complex, ambiguous business problems with AI-driven solutions.

Responsibilities

  • Design and Deploy Enterprise AI Agents: Lead the end-to-end design, build, and delivery of LLM-powered agents that perform reasoning, planning, and multi-step task execution across tools, APIs, and sensitive enterprise data sources with enterprise-grade reliability, observability, and performance metrics.
  • Translate Business Problems into Technical Solutions: Work directly with enterprise customers to translate high-value, ambiguous business requirements into well-framed agentic workflows with clear success criteria, evaluation methodologies, and measurable business outcomes.
  • Build Production Features for North Platform: Contribute to the development and shipping of features for Cohere's North AI workspace platform, working across the full product lifecycle from conceptualization through production deployment, ensuring enterprise-grade security and reliability.
  • Own Use Cases End-to-End: Take complete ownership of scoping and shaping use cases from inception to completion, demonstrating flexibility across technical domains including backend, frontend, and infrastructure to deliver optimal solutions tailored to specific business needs.
  • Build Robust Evaluation Frameworks: Develop comprehensive evaluation frameworks and measurement systems for agent performance, moving beyond trial-and-error approaches to systematically measure accuracy, safety, latency, and reliability of AI systems.
  • Establish Shared Engineering Patterns: Contribute to the development of shared frameworks, architectural patterns, and best practices that enable consistent, high-quality delivery of agentic workflows across multiple customer engagements and engineering teams.
  • Drive Technical Leadership and Clarity: Build alignment across cross-functional stakeholders in ambiguous situations, raise engineering quality standards across the organization, and lead technical discussions with enterprise decision-makers and engineering teams.
  • Customer-Focused On-Site Engagement: Travel to customer locations 20-40% of the time to collaborate directly with enterprise teams, conduct technical workshops, implement solutions, and ensure successful deployment of AI agents in production environments.

Qualifications

What we look for.

Technical

  • Production Python Development

    Advanced proficiency in Python with demonstrated ability to write clean, testable, observable, and scalable production code that meets enterprise-grade reliability standards.

  • LLM Application Architecture

    Hands-on experience architecting and deploying production-grade large language model applications including foundational knowledge of frontier models, their capabilities, limitations, and deployment considerations.

  • RAG and Agentic Workflow Development

    Proven expertise building and deploying retrieval-augmented generation (RAG) systems and agentic applications with multi-step reasoning patterns such as ReAct, Plan-and-Execute, and tool-use orchestration.

  • Vector Databases and Semantic Search

    Deep familiarity with vector database technologies, semantic search implementations, and embedding models used in modern LLM stacks for efficient information retrieval.

  • LLM Orchestration Frameworks

    Strong expertise with LLM orchestration and agentic frameworks such as LangChain, CrewAI, or similar tools for managing complex LLM workflows and multi-agent systems.

  • Evaluation Framework Development

    Demonstrated ability to design and implement robust evaluation methodologies including metrics definition, A/B testing, performance measurement, and safety validation for AI systems.

  • System Observability and Monitoring

    Experience implementing comprehensive observability solutions for production systems including logging, tracing, metrics collection, and real-time monitoring of agent behavior and performance.

  • API Integration and Data Pipeline Design

    Proven expertise integrating third-party APIs, designing robust data pipelines, and managing information flow between disparate systems while maintaining security and data governance.

Education

  • Bachelor's Degree in Computer Science or Related Field

    Formal qualification in Computer Science, Software Engineering, Mathematics, Physics, or equivalent practical experience demonstrating strong foundational computer science knowledge.

  • Continuous Learning in AI/ML

    Demonstrated commitment to staying current with advances in large language models, AI architecture patterns, and emerging agentic frameworks through formal learning, research, or open-source contributions.

Experience

  • Enterprise Software Development

    5+ years of experience building and deploying production software systems, with demonstrated success owning features from conception through production deployment in enterprise environments.

  • Applied AI and Machine Learning

    3+ years of hands-on experience with applied AI, machine learning systems, or LLM applications in production environments, including experience with model evaluation and optimization.

  • Customer-Facing Technical Leadership

    Proven track record working directly with enterprise customers, conducting technical discovery sessions, scoping complex requirements, and translating business needs into concrete technical specifications.

  • Cross-Functional Problem Solving

    Demonstrated ability to own use cases end-to-end, working flexibly across multiple technical domains (backend, frontend, DevOps) to deliver optimal solutions in ambiguous environments.

  • Startup or Fast-Paced Environment Experience

    Proven success operating effectively in startup-pace environments characterized by rapid iteration, shifting priorities, and high ambiguity while maintaining engineering quality.

Skills

Required

  • Python

    Expert-level Python development with focus on writing production-quality, testable, and maintainable code

  • Large Language Models (LLMs)

    Deep understanding of LLM capabilities, limitations, fine-tuning strategies, and deployment considerations in enterprise environments

  • Prompt Engineering

    Advanced prompt engineering techniques including few-shot learning, chain-of-thought, and structured output formatting for optimizing LLM behavior

  • Retrieval-Augmented Generation (RAG)

    Hands-on implementation of RAG pipelines including document chunking, embedding generation, vector search, and context injection

  • Agentic AI Systems

    Practical experience building autonomous agents with tool-use capabilities, multi-step reasoning, and decision-making frameworks

  • Agent Evaluation and Testing

    Systematic approach to measuring agent performance including accuracy metrics, safety validation, latency profiling, and production observability

  • Software Engineering Fundamentals

    Strong foundation in system design, data structures, algorithms, testing strategies, and debugging techniques

  • API Design and Integration

    Expertise in RESTful API design, third-party API integration, and building robust interfaces for LLM-powered systems

Preferred

  • Regulated Industry Experience

    Nice to have

    Prior experience working in regulated industries such as finance, healthcare, or telecommunications with understanding of compliance, security, and auditability requirements

  • Enterprise AI Security and Compliance

    Nice to have

    Demonstrated knowledge of enterprise AI security practices, data governance, model governance frameworks, and compliance requirements for sensitive data handling

  • Architectural Standards Development

    Nice to have

    Experience establishing architectural standards, best practices, and governance frameworks for AI systems across distributed teams

  • Full-Stack Development

    Nice to have

    Comfort and demonstrated competency flexing into unfamiliar technical areas including frontend frameworks, DevOps, or infrastructure as code when problems require it

  • Open Source Contributions

    Nice to have

    Active contributions to open-source projects, particularly LLM frameworks, AI libraries, or developer tools demonstrating community engagement and technical depth

  • Research and Innovation

    Nice to have

    Background in AI research, published papers, or participation in emerging AI architecture discussions demonstrating thought leadership

  • Customer Engineering Experience

    Nice to have

    Prior experience as a forward-deployed engineer, solutions architect, or customer engineering role involving on-site customer collaboration

  • Technical Public Speaking

    Nice to have

    Experience presenting technical content to enterprise audiences, leading workshops, or communicating complex AI concepts to non-technical stakeholders

Tech stack

Languages

PythonTypeScript/JavaScriptSQL

Frameworks

LangChainLLaMA Index (formerly GPT Index)FastAPIReactPydantic

Databases

Vector Databases (Pinecone, Weaviate, Milvus)PostgreSQLDocument Stores (MongoDB, Firestore)

Tools

Git/GitHubDockerKubernetesPrompt Engineering Tools (Langfuse, LlamaIndex Studio)Observability Platforms (Datadog, New Relic, OpenTelemetry)API Testing Tools (Postman, Insomnia)

Other

OpenAI API, Claude API, Cohere APIEnterprise Integration PatternsSecurity and Compliance StandardsTesting Frameworks (pytest, unittest)CI/CD Pipelines

Compensation

Pay and benefits.

Base·USD 180,000 – 280,000

Equity·Stock options

Full posting

Original listing.

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!


About North:

North is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications.


Why this role?

This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications.

We’re looking for Software Engineers with Applied AI experience who can own the design, build, and deployment of agentic workflows powered by Large Language Models (LLMs), from early prototypes to production-grade AI agents, to deliver concrete business value in enterprise workflows. You’ll work closely with customers on real-world business problems, often building first-of-their-kind agent workflows that integrate LLMs with tools, APIs, and data sources. While our pace is startup-fast, the bar is enterprise-high: agents must be reliable, observable, safe, and auditable from day one.

Note: between 20 - 40% travel anticipated.


In this role, you will:

  • Work closely with our enterprise customers to translate high-value, ambiguous business problems into well-framed agentic workflows with clear success criteria and evaluation methodologies

  • Lead the design, build, and delivery of LLM-powered agents that reason, plan, and act across tools, APIs, and sensitive enterprise data sources, with enterprise-grade reliability and performance

  • Build and ship features for North, our AI workspace platform, working across the full product lifecycle from conceptualisation through production

  • Take ownership of scoping and shaping use cases end-to-end, flexing into whatever technical area the problem demands (including frontend) to drive the most effective solution

  • Contribute to shared frameworks and patterns that enable consistent, high-quality delivery across customers and teams

  • Drive clarity in ambiguous situations, build alignment, and raise engineering quality across the organization

  • Travel up to 20–40% to work on-site with customers and partners


You may be a good fit if:

  • You have hands-on experience building and deploying production-grade software in Python; you write clean, testable, observable, scalable code

  • You've built and deployed highly performant RAG and agentic applications, including agents that plan and execute multi-step tasks using patterns like ReAct or Plan-and-Execute

  • You're deeply familiar with the LLM stack: frontier models, vector databases, and orchestration frameworks

  • You have a proven ability to build robust evaluation frameworks, moving well beyond trial and error, to measure agent accuracy, safety, and latency

  • You’re experienced working directly with customers and can lead technical discussions with enterprise stakeholders, translating ambiguous business needs into concrete technical specs

  • You have experience owning the full scope of a use case end-to-end

  • You thrive in fast-paced and ambiguous environments and can execute well even when priorities are shifting


It's a bonus if you have:

  • Experience setting architectural standards for AI and agentic systems across distributed teams

  • Experience flexing into unfamiliar technical areas, such as frontend, when the problem calls for it

  • Exposure to regulated or sensitive industry environments (finance, healthcare, telecoms)

  • Experience with enterprise security, compliance, or auditability requirements for AI systems

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 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.

Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers page.

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