Large language model generative ai Work, Jobs (with Salaries)

AI Large Language Model (LLM) Engineer
Accenture —London
- Full-time
- Computer Science
- Engineering
- Master's degree
AI Large Language Model (LLM) Technology Architect
Accenture —London
- Full-time
- Master's degree
- Bachelor's degree
- Machine learning
AI Creative Producer
ElevenLabs —London
- Full-time
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- Social media management
Conversational AI Chat Bot Developer, Cognigy
TTEC Digital —London
- Full-time
- Remote
- Java
- Master's degree
- JavaScript
Quick apply
5d
AI Research Engineer (Model Compression & Quantization)
Tether Operations Limited —London
- Full-time
- Remote
- Doctoral degree
- Computer Science
- English
AI Large Language Mode (LLM) Technology Lead/Principal Architect
Accenture —London
- Full-time
- Master's degree
- Bachelor's degree
- Machine learning
Natural Language Processing Researcher
G-Research —London
- Bar
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- Master's degree
- Annual leave
Forward Deployed Engineer III, Generative AI (French, German)
Google —London
- Doctoral degree
- Computer Science
- Master's degree
AI Adoption Consultant
Innovecture —London
- Microsoft Powerpoint
- Microsoft Word
- Microsoft Excel
Quick apply
AI Engineer (Fluent Portuguese & English)
Chubb —London
- Full-time
- Hybrid work
- English
- Master's degree
- Financial services
- Annual leave
- Employee assistance programme
Sr Product Manager (Portuguese), AI Shopping, International
Amazon Development Centre (London) Limited —London
- Full-time
- Bilingual
- English
- Business development
AI Engineer (UK)
Meltwater Group —Remote
- Remote
- Azure
- Computer Science
- Master's degree
- Annual leave
11d
Strategy Senior Associate - AI Enablement: Solutions & Client Enablement
JPMorganChase —London
- Full-time
- Microsoft Powerpoint
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Gen AI Lead
Elance India —London
- £300.20 - £400.02 a day
- Full-time
- DevOps
- Java
- Master's degree
Quick apply
Generative AI Engineer
Bridewell —London
- Full-time
- Hybrid work
- Analysis skills
- JavaScript
- Travel
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AI Engineering Intern
Medpace, Inc. —London
- Full-time
- Doctoral degree
- Computer Science
- Master's degree
- Annual leave
- Employee discount
1d
Business Development Manager(s) — Conferences & AI Platform Technologies
Insilico Medicine —Remote
- Remote
- Sales
- Salesforce
- Presentation skills
Founder Advocate, EMEA Startup, Google Cloud
Google —London
- £176,000 - £181,000 a year
- Computer Science
- Engineering
- English
13d
AI Deployment Engineer, Large Enterprise
OpenAI —London
- Full-time
- Hybrid work
- Sales
- Machine learning
- JavaScript
- Relocation assistance
Gen AI Developer
NTT Ltd —London
- Azure
- Java
- AWS

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AI Large Language Model (LLM) Engineer

Accenture -
London

Apply Now

Job details

Full-time

Qualifications

Law
Computer Science
Engineering
Master's degree
Bachelor's degree
Machine learning
Deep learning
Natural language processing
AI
Python

Full job description

As a hands on AI Engineer, you will be at the heart of designing and building the components that make up advanced AI systems powering the modern enterprise. This is a deeply technical, hands-on engineering — you will spend the majority of your time in the detailed design, development, integration, and testing of AI system components across classical machine learning, generative AI, and agentic systems, delivering these within active client engagements.

You will take detailed architecture and design specifications and translate them into working, production-quality software components. This means writing clean, well-structured code, making low-level design decisions within your assigned scope, and ensuring your components integrate reliably within the broader AI system. You will build and wire together the constituent parts of AI agent systems — including individual agent logic, tool integrations, skills, and memory components — and contribute to the development and integration of foundation and classical ML models into end-to-end pipelines.

A hands-on curiosity for the open source ecosystem is essential in this . You will continuously evaluate, learn, and adopt relevant open source libraries and frameworks — such as those spanning agent orchestration, vector storage, model serving, and ML pipelines — selecting and applying the right ones for the problem at hand. Equally, you will configure, integrate, and operationalize third-party AI technologies and platform services, understanding their capabilities and constraints deeply enough to make them work reliably within the context of a larger enterprise system. You will engineer components with enterprise-grade qualities in mind, ensuring your work meets defined requirements across security, observability, governance, performance, and scalability. You will write and maintain the technical artifacts that accompany your engineering work — including low-level design documents, component specifications, and integration contracts — ensuring your work is well-documented, testable, and handoff-ready. You will operate as a practitioner within cross-functional delivery teams alongside data engineers, ML engineers, and application developers, taking direction from lead and principal architects while contributing meaningfully to technical problem-solving and design discussions within your domain. This is an opportunity to build deep, hands-on expertise across the AI engineering stack, develop strong software engineering fundamentals applied to cutting-edge AI systems, and grow toward a lead engineer or architect over time.

THE WORK

Design, build, and configure individual agents — including their prompts, tools, and skills — and integrate them into multi-agent workflows

Implement agent orchestration logic that handles task handoffs, communication, and error recovery

Build evaluation harnesses and test suites that measure agent and component quality on metrics such as accuracy, relevance, and faithfulness, and share findings to inform design improvements

Integrate foundation models into applications, selecting the appropriate model and invocation pattern for each use case

Build and run model fine-tuning pipelines — including data preparation and training — to adapt models to specific business domains, applying working knowledge of transformer-based architectures

Build ingestion pipelines that parse, chunk, enrich, and index unstructured enterprise content for retrieval

Implement embedding generation, integrate vector databases, and develop retrieval components, including connectors and adapters that process unstructured content into end-to-end RAG pipelines

Build the logic that assembles prompts and manages what information is passed to the model within its context window

Implement memory components that store and recall conversational history and other relevant context

Implement input/output guardrails, content filtering, and defenses against prompt injection

Build PII detection and redaction components and integrate access controls for model and tool access

Implement versioning, audit logging, and lineage tracking, and maintain model documentation that keeps the system auditable

Instrument components with logging and tracing for requests, responses, token usage, and tool calls

Contribute to monitoring, alerting, and cost tracking that keep AI systems healthy in production

Continuously learn and apply new design patterns, technologies, and frameworks across the fast-evolving AI landscape, bringing fresh approaches to the components you build

Collaborate within cross-functional teams to clarify requirements and ensure your components meet stakeholder needs

Create and maintain clear technical documentation for the components you build, supporting troubleshooting and future development

EDUCATION

Bachelor's Degree in Computer Science, Computer Engineering, Data Science, or a related engineering discipline

BASIC (REQUIRED) QUALIFICATION

Experience (work or coursework) in designing, coding, building advanced AI solutions using agentic, generative and classical AI/ML using at least one cloud vendor.

Experience (work or coursework in the Agentic, LLM and Generative AI space.

Experience (work or coursework) architecting and operationalizing LLM driven application architecture patterns.

Experience in coding and engineering, machine learning, deep learning and NLP solutions and applications.

Coding experience using Python

Apply Now

Refine Your Search

large language model generative ai jobs

AI Large Language Model (LLM) Engineer

AI Large Language Model (LLM) Technology Architect

AI Creative Producer

Conversational AI Chat Bot Developer, Cognigy

AI Research Engineer (Model Compression & Quantization)

AI Large Language Mode (LLM) Technology Lead/Principal Architect

Natural Language Processing Researcher

Forward Deployed Engineer III, Generative AI (French, German)

AI Adoption Consultant

AI Engineer (Fluent Portuguese & English)

Sr Product Manager (Portuguese), AI Shopping, International

AI Engineer (UK)

Strategy Senior Associate - AI Enablement: Solutions & Client Enablement

Gen AI Lead

Generative AI Engineer

AI Engineering Intern

Business Development Manager(s) — Conferences & AI Platform Technologies

Founder Advocate, EMEA Startup, Google Cloud

AI Deployment Engineer, Large Enterprise

Gen AI Developer

I want to receive the latest job alerts for large language model generative ai

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