Frontier Engineer

Cognizant; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Cognizant in London is seeking a Frontier Engineer to design, deploy and continuously improve AI-native systems for leading clients. You will collaborate with a lean pod to build multi-agent AI solutions and translate bold ideas into production-ready capabilities.

The role emphasizes AI tool fluency, prompt engineering and responsible AI practices, with a hybrid work model requiring three days per week in an office in London.

Qualifications

• 3-10 years of technical delivery experience with strong AI-tool fluency across the full stack.
• Hands-on experience with agentic coding and multi-agent orchestration using LangChain, AutoGen or LangGraph.
• Strong prompt and intent engineering skills, with the ability to validate AI-generated code.
• Experience designing RAG pipelines and managing vector databases to ground and improve agent accuracy.
• LLMOps and model lifecycle management experience, including guardrail implementation, AIOps observability and CI/CD for AI systems.

Responsibilities

• Build and orchestrate multi-agent AI systems, integrating agent outputs into production environments that solve real business problems.
• Design intent-driven prompts and workflows for AI coding agents, applying human judgment to validate quality, safety and accuracy.
• Create scalable RAG architectures, vector stores and knowledge systems that enable trustworthy and context-aware AI experiences.
• Deploy, monitor and optimize LLMs and AI agents in production, implementing responsible AI guardrails and observability practices.
• Build AI-embedded applications and workflows using enterprise AI platforms, automation tools and modern engineering practices.

Skills

AI delivery experience

LLMOps experience

Context retrieval engineering

Business-outcome orientation

Agentic engineering

Tools

LangChain

AutoGen

LangGraph

Vector databases

CI/CD for AI

Job description

About the role

As a Frontier Engineer, you'll help build AI that moves the world forward. Working at the frontier of technology, you'll join a lean, high-impact pod where human ingenuity and AI come together to solve real-world challenges for some of the world's leading organizations. You'll partner directly with clients to design, deploy and continuously improve AI-native systems, with the freedom to experiment with emerging technologies and turn bold ideas into real impact.

In this role, you will

• Build and orchestrate multi-agent AI systems, integrating agent outputs into production environments that solve real business problems.

• Design intent-driven prompts and workflows for AI coding agents, applying human judgment to validate quality, safety and accuracy.

• Create scalable RAG architectures, vector stores and knowledge systems that enable trustworthy and context-aware AI experiences.

• Deploy, monitor and optimize LLMs and AI agents in production, implementing responsible AI guardrails and observability practices.

• Build AI-embedded applications and workflows using enterprise AI platforms, automation tools and modern engineering practices.

Work model

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role's business requirements, this is a hybrid position requiring 3 days a week in a client or Cognizant office in London, United Kingdom. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.

What you must have to be considered

• 3-10 years of technical delivery experience with strong AI-tool fluency across the full stack.

• Hands-on experience with agentic coding and multi-agent orchestration using frameworks such as LangChain, AutoGen or LangGraph.

• Strong prompt and intent engineering skills, with the ability to validate AI-generated code for quality and correctness.

• Experience designing RAG pipelines and managing vector databases to ground and improve agent accuracy.

• LLMOps and model lifecycle management experience, including guardrail implementation, AIOps observability and CI/CD for AI systems.

These will help you succeed

• Demonstrated agentic engineering and orchestration expertise paired with strong context and retrieval engineering.

• Production AI operations (LLMOps) experience running LLMs and agents at scale.

• A track record of full-stack AI delivery, reaching for an AI tool first as a generalist builder.

• Domain fluency and contextual judgment to validate AI outputs against real business context.

• A strong business-outcome orientation, owning what the pod builds permanently in production.

We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.

Cognizant is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.