Forward Deployed Engineer, Agentic Platform (UK Public Sector)

Forward Deployed Engineer · Senior · Full Time · Remote

United Kingdom · RemoteGBP 110k – 155k5d ago
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Role

What you'll do.

Forward Deployed Engineer at Cohere tasked with designing, building, and deploying production-grade Large Language Model-powered agentic workflows for enterprise customers in the UK public sector. This role bridges Cohere's North AI workspace platform with client engineering teams, requiring deep expertise in applied AI, Python development, RAG systems, and LLM orchestration to solve complex business problems in regulated industries including finance, healthcare, and telecommunications. You'll own end-to-end delivery of AI agents from prototype to production while maintaining enterprise-grade reliability, security, and auditability standards.

Responsibilities

  • Enterprise AI Workflow Design and Implementation: Collaborate directly with enterprise customers to translate complex, ambiguous business problems into well-defined agentic workflows with clear success criteria. Design and build LLM-powered agents that reason, plan, and execute multi-step tasks across tools, APIs, and sensitive enterprise data sources using patterns such as ReAct and Plan-and-Execute, ensuring enterprise-grade reliability and performance at scale.
  • Full Product Lifecycle Ownership: Lead development from conceptualization through production for North, Cohere's AI workspace platform. Own the complete scope of assigned use cases end-to-end, flexing into whatever technical area the problem demands, including frontend development, to architect and deliver the most effective solutions for customer needs.
  • Agentic Systems Quality Assurance: Build and maintain robust evaluation frameworks for measuring agent accuracy, safety, latency, and auditability. Move beyond trial-and-error methodologies to establish systematic evaluation methodologies and observability standards, ensuring deployed agents meet reliability and security requirements for regulated industries.
  • Engineering Standards and Framework Development: Contribute to and establish shared frameworks, architectural patterns, and best practices that enable consistent, high-quality delivery across customers and distributed engineering teams. Drive clarity in ambiguous situations, build cross-functional alignment, and elevate engineering quality standards across the organization.
  • Customer Technical Leadership: Lead technical discussions and translate business requirements with enterprise stakeholders, demonstrating deep customer empathy and communication skills. Travel 20-40% on-site to work directly with customers and partners, providing hands-on technical guidance and ensuring successful agentic system deployment in production environments.
  • Production-Grade Code Development: Write clean, testable, observable, and scalable Python code that powers production agentic systems. Implement best practices for code quality, testing, logging, and monitoring to ensure deployed AI systems remain reliable, maintainable, and auditablein enterprise environments.

Qualifications

What we look for.

Technical

  • Production Python Development

    Hands-on expertise building and deploying production-grade software in Python with demonstrated ability to write clean, testable, observable, and scalable code that meets enterprise reliability standards.

  • RAG and Agentic Systems Architecture

    Proven experience designing and deploying highly performant Retrieval-Augmented Generation (RAG) and agentic applications, including autonomous agents that plan and execute multi-step tasks using established orchestration patterns like ReAct and Plan-and-Execute.

  • Large Language Model Stack Proficiency

    Deep familiarity with the complete LLM ecosystem including frontier models, vector databases, embedding systems, and LLM orchestration frameworks. Understanding of model capabilities, limitations, and practical implementation considerations for enterprise deployments.

  • Evaluation Framework Development

    Proven ability to design and implement robust evaluation frameworks for AI systems that measure agent accuracy, safety, latency, and auditability. Experience with metrics, benchmarking, and systematic testing methodologies beyond exploratory approaches.

  • Enterprise System Integration

    Experience integrating AI systems with enterprise tools, APIs, data sources, and infrastructure. Understanding of security considerations, data governance, and compliance requirements when connecting LLMs to sensitive business systems and databases.

Education

  • Computer Science or Related Field

    Bachelor's degree in Computer Science, Software Engineering, AI/Machine Learning, or equivalent practical experience demonstrating strong foundational knowledge in software engineering principles and applied AI systems.

Experience

  • Applied AI and ML Systems Development

    5+ years of professional experience building applied AI and machine learning systems in production environments, with significant focus on LLM-powered applications, agentic systems, or generative AI in the last 2-3 years.

  • Enterprise Customer Engagement

    Demonstrated experience working directly with enterprise customers, leading technical discussions with C-level stakeholders, and translating ambiguous business requirements into concrete technical specifications and implementations.

  • End-to-End Product Ownership

    Track record of owning complete product features or systems from conception through deployment, including responsibility for architecture decisions, implementation, testing, and post-launch monitoring and optimization.

  • Regulated Industry Experience (Preferred)

    Exposure to working in regulated or security-sensitive industry environments such as finance, healthcare, telecommunications, or government sectors, with understanding of compliance, auditability, and security requirements specific to these domains.

Skills

Required

  • Python

    Expert-level Python development with strong foundations in software architecture, testing, and code quality practices for production systems.

  • Large Language Models (LLMs)

    Deep practical experience with frontier LLM APIs, fine-tuning, prompting strategies, chain-of-thought reasoning, and deployment considerations for enterprise applications.

  • Agentic AI Systems

    Hands-on expertise designing and implementing autonomous agents with planning, reasoning, and tool-use capabilities using frameworks like LangChain, LlamaIndex, or similar orchestration platforms.

  • Retrieval-Augmented Generation (RAG)

    Practical experience building RAG systems including vector embeddings, semantic search, knowledge base integration, and optimization for accuracy and relevance in production environments.

  • Vector Databases

    Working knowledge of vector database systems such as Pinecone, Weaviate, Milvus, or similar technologies for efficient semantic search and knowledge retrieval in AI applications.

  • System Design and Architecture

    Ability to design scalable, reliable systems that integrate multiple components including LLMs, APIs, databases, and enterprise tools while considering security, observability, and performance requirements.

  • Stakeholder Communication

    Strong ability to translate technical concepts for non-technical audiences, lead discussions with enterprise stakeholders, and discover requirements in ambiguous business contexts.

Preferred

  • LLM Orchestration Frameworks

    Nice to have

    Experience with platforms like LangChain, LlamaIndex, Guidance, or similar frameworks for managing complex LLM workflows and agent behaviors at scale.

  • Prompt Engineering and Optimization

    Nice to have

    Advanced experience crafting effective prompts, few-shot learning strategies, and systematic prompt optimization techniques to improve model performance and reliability.

  • Observability and Monitoring

    Nice to have

    Experience implementing comprehensive logging, tracing, and monitoring solutions for AI systems to ensure auditability, debuggability, and compliance with regulatory requirements.

  • Frontend Development

    Nice to have

    Familiarity with frontend frameworks and technologies allowing you to flex into full-stack ownership when architectural requirements demand it across your projects.

  • Finance, Healthcare, or Telecommunications Domain Knowledge

    Nice to have

    Prior experience or exposure to regulated industry sectors with understanding of compliance requirements, security standards, and business-specific challenges in these verticals.

  • Active DV Security Clearance

    Nice to have

    Active Developed Vetting (DV) security clearance or eligibility to obtain clearance for UK government and public sector projects, providing significant advantage for this role.

  • API Design and Integration

    Nice to have

    Experience designing and integrating with RESTful or GraphQL APIs, managing authentication, rate limiting, and robust error handling across distributed systems.

  • Machine Learning Operations (MLOps)

    Nice to have

    Practical experience with ML monitoring, model versioning, experiment tracking, and deployment pipelines for maintaining production AI systems reliably.

Tech stack

Languages

PythonTypeScript/JavaScriptSQL

Frameworks

LangChainLlamaIndexFastAPIReact

Databases

Vector Databases (Pinecone, Weaviate, Milvus)PostgreSQLRedis

Tools

Cohere North PlatformGit and GitHubDocker and KubernetesDatadog or Similar APMPrompt Engineering Tools

Other

Large Language Model APIsCloud Platforms (AWS, GCP, Azure)Security and Compliance PracticesTesting and Evaluation Frameworks

Compensation

Pay and benefits.

Base·GBP 110,000 – 155,000

Benefits

  • Comprehensive Health and Wellness Coverage

    Full health and dental benefits including vision coverage, with a separate mental health budget to support employee wellbeing and preventive care.

  • Generous Paid Time Off

    Six weeks of paid vacation (30 working days annually), significantly above UK industry standards, supporting work-life balance and employee recovery.

  • Parental Leave Support

    100% parental leave top-up for up to six months for either parent, demonstrating commitment to family-friendly policies and supporting diverse family structures.

  • Retirement and Pension Benefits

    RRSP matching for Canadian employees, 401K for US employees, and Pension Scheme participation for UK employees with competitive contribution rates.

  • Wellness and Enrichment Benefits

    Annual enrichment budget covering arts and culture, fitness and wellness programs, quality time initiatives, and workspace improvement credit for personalized work environments.

  • Professional Development and Learning

    Education and learning stipend for conferences, courses, certifications, and executive coaching to support continuous skill development in emerging AI technologies.

  • Home Office and Workspace Stipend

    500 USD home office stipend for remote workers to establish proper workspace setup, plus co-working benefits for those not near an office location.

  • Meal and Lunch Benefits

    Weekly lunch stipend of 75 GBP (or equivalent in local currency), plus daily lunch programs and regular snacks for in-office employees to support nutrition and camaraderie.

  • Global Office Access and Travel

    Budget for traveling to other Cohere offices when remote, plus annual company offsite events, enabling cross-functional collaboration and global team connection.

  • Flexible Work Arrangements

    Remote-friendly work culture with options to work from home or from Cohere offices in London, Toronto, New York City, San Francisco, Montreal, Paris, Berlin, and Seoul.

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.

Location: UK

Active DV clearance is highly preferred

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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