1 to 25 of 121 Permanent LLM Jobs in the City of London

Exposure to downstream customer platforms and trading ERP systems. Experience with platforms such as Azure ML Studio, Foundry, and Databricks Mosaic. Familiarity with NLP, LLM deployment, Agentic AI frameworks (MCP, A2A, N8N), and retrieval-augmented generation (RAG) systems. Roles and Responsibilities: Lead the end-to-end development and delivery ...

software engineering, or data engineering. Programming experience (especially Python) Experience writing clean, maintainable Python code. Applied AI experience such as exposure to LLM APIs (OpenAI, Azure OpenAI, Anthropic, etc.) and experience with small personal or internship projects building agents or AI-driven workflows. Agentic frameworks in Python is a plus ...

encryption at rest and in transit, and secrets management (AWS Secrets Manager, HashiCorp Vault). • Develop and enforce governance frameworks for working with LLM APIs and AI services, including data protection, PII safeguards, and compliance requirements. • Conduct security audits, vulnerability assessments, and implement remediation strategies to maintain a secure infrastructure. ...

architecture. • Cloud Expertise : Architectural expertise with one primary cloud platform (Azure, GCP, or AWS) and hands-on familiarity with at least one other. • GenAI & LLM Depth : Demonstrated experience architecting and guiding solutions using GenAI platforms (e.g., Azure OpenAI, Vertex AI, or AWS Bedrock). • RAG & Orchestration : Proven experience designing complex ...

methods – automating testing and evaluation of both deterministic and generative AI conversations. Required Skills Must Have Python – minimum 2+ years experience building production-grade LLM applications. Strong software engineering fundamentals, including microservices architecture, CI/CD pipelines, and event-driven architecture. AI Engineering experience including: RAG pipelines Prompt engineering Vertex ...

digital therapeutics, or regulated healthtech Deployed LLMs or predictive models in production environments Familiarity with FHIR, HL7, or secure health data pipelines Hands-on LLM work: prompt engineering, RAG, fine-tuning (LoRA/QLoRA) The Package Competitive salary + meaningful equity Work directly with and be mentored by two highly ...

120k Base Salary + Discretionary Bonus + Equity Zettafleet is an end-to-end platform for businesses and organisations to train their own LLM on their proprietary data. We can use non-conventional AI hardware and automatically source and combine GPUs (and other types of AI accelerators) from multiple cloud ...

Cloud provider Pulumi - Infrastructure as Code (TypeScript) GitHub Actions - CI/CD Firebase - Feature flags Cloudflare - CDN and DNS AI & Machine Learning Python BAML - LLM prompt engineering DSL Vertex - ML Ops Why Join Us This is a ground-floor opportunity to shape the product and the codebase from day one. ...

workflows and agents. AI Expertise Solid understanding of modern AI concepts and patterns developed over the last few years. Experience in LLM orchestration, agent frameworks, prompt engineering and real‐world delivery. An “eye for making it work” — practical, production‐focused engineering. Ways of Working Able to step into an environment ...

debate and align to unified decisions. Own operability: CI/CD, monitoring/alerting, performance optimisation, safe rollbacks. Build and integrate AI features (LLM/agent workflows, RAG/vector DB integration, eval hooks, cost/safety guardrails). Help evolve our reusable product templates and shared architecture across ...

business strategy, enterprise standards, and regulatory requirements. Key Responsibilities: Enterprise AI Architecture & Roadmap: Define and maintain the AI reference architecture and implementation roadmap, covering LLM platforms, data pipelines, knowledge graphs, APIs, microservices, and event-driven architectures across hybrid cloud environments. Governance & Standards: Establish AI governance frameworks, policies, and playbooks ...

design patterns AI/ML Infrastructure Feature engineering architecture ML pipeline and deployment workflows Experience supporting production ML systems Familiarity with embeddings, vector databases, LLM orchestration (desirable) Data observability and model monitoring Platform & DevOps CI/CD for data workflows Git-based engineering standards Docker/containerisation Infrastructure-as-code ...

scalable API platforms. Key Responsibilities Own the technical strategy and execution across the company’s core products, including real-time APIs, data pipelines, and LLM-powered analytics. Collaborate closely with Product and Data Science to deliver a forward-thinking technology roadmap. Lead, mentor, and scale a high-performing engineering team ...

Base Salary + Discretionary Bonus + Equity About Zettafleet Zettafleet is an end-to-end platform for businesses and organisations to train their own LLM on their proprietary data. We can use non-conventional AI hardware and automatically source and combine GPUs (and other types of AI accelerators) from multiple ...

Data & NLP, you will: Own and improve search performance (precision & recall) Optimise large-scale search algorithms for speed and relevance Design and implement agentic LLM workflows Build and maintain robust data pipelines Lead model development, training, and deployment Provide technical leadership across ML and NLP initiatives This is a high ...

research and engineering domains. Core Skills Strong foundation in deep learning and transformer-based architectures. Hands-on experience with PyTorch and modern NLP/LLM toolchains. Deep knowledge of parameter-efficient fine-tuning methods (LoRA, adapters, PEFT techniques). Expertise in intent classification, evaluation metrics (precision, recall, F1), and experimental ...

Engineer to help scale their NLP and search capabilities . What you'll be doing • Improving search quality (precision & recall) across large datasets • Designing LLM-powered workflows and agentic systems • Building ML models and NLP pipelines for production use • Working with large-scale search infrastructure (Elasticsearch/OpenSearch) • Collaborating with ...

/agent systems. Qualifications 8+ years of software engineering experience (6+ with MS degree). 2+ years focused on ML/AI systems or LLM-driven applications. Demonstrated technical leadership and ownership of systems end-to-end. Experience handling production incidents and operational processes. Proven ability to influence technical direction ...

with success selling AI-led transformation programs . Deep experience in solution selling rather than product selling. Demonstrated success in selling: Generative AI and LLM-based enterprise solutions Predictive and prescriptive analytics Intelligent Automation (RPA + AI) Data Engineering, MLOps, and AI platforms Ability to articulate AI ethics, governance, security ...

troubleshoot ontology logic and query performance. Desired Experience Familiarity with metadata standards (Dublin Core, schema.org). Experience integrating semantic technologies with AI/LLM workflows. Proven track record of embedding semantic layers into enterprise systems. Hands-on with tools like Protégé, semantic reasoners, or cloud-based graph services (AWS Neptune ...

legal environment. This is a deeply hands-on engineering role focused on shipping reliable systems used by real customers. Key responsibilities Build and deploy LLM-powered features across drafting, prosecution, and litigation workflows Design and maintain RAG pipelines over large, complex legal and technical corpora Own systems from prototype through ...

modelling Daily user of AI-assisted development tools with demonstrated productivity impact Strong communication skills and a passion for mentoring engineers Desirable: Experience deploying LLM-based applications or multi-agent AI systems Familiarity with agentic frameworks and prompt engineering Previous team lead or tech lead role with team ownership Experience ...

this opportunity is for you! What We’re Looking For: Previous experience supporting the creation of Agentic AI Agents Expertise in Generative AI and LLM selection. Strong background in decision support and conversational AI. Familiarity with engineering prompts and agent patterns. Knowledge of cloud standards and privacy governance. Experience ...

. The Full Stack Engineer will not just use AI tools but actually build with them. The Full Stack Engineer will integrate cutting-edge LLM workflows. The Full Stack Engineer will build AI-powered product features. The Full Stack Engineer will develop front end solutions using React, Typescript, NextJS. ...

consistent under load Systems designed to scale confidently from 10 → 10,000+ users Tech Stack NodeJS GraphQL (NestJS) PostgreSQL Prisma GCP Terraform AI/LLM integrations (including Gemini) What They’re Looking For Strong fundamentals: data structures, OOP, and complexity analysis Experience building high-concurrency, event-driven systems Reliability mindset ...