176 to 200 of 222 Retrieval-Augmented Generation Jobs in the South East

feedback loops. 25% Architect & scale Own reliability, latency, and cost. Design online/offline eval harnesses, canaries, and SLAs; operate GPUs/accelerators where needed. Stand up and harden RAG pipelines (indexing, retrieval policies, grounding, guardrails) and agent frameworks. Take basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost … building production ML/back‐end systems; 2+ years leading while coding. Expert Python ; strong back‐end chops (e.g., FastAPI, gRPC, Postgres, pub/sub/streams). Agents & RAG: Fluency with at least one agent framework ( ADK preferred ). Proven track record shipping AI agents and building RAG pipelines. LLM + DS depth: Prompting/tooling, retrieval More ❯

Full Stack AI Software Engineer - Full Remote UK - £90,000 + Equity This role requires a software engineer with experience in implementing RAG pipelines and Vector Search (and hybrid AI searches, preferably). The client I am working with is an AI focused start-up backed by a £1.7M pre-seed investment. They are on a mission to streamline the … an early stage. What you'll work on: Backend APIs (Python/FastAPI): Build and maintain secure, high-performance services that drive AI features and data access at scale. RAG & vector search: Design and improve retrieval pipelines (embeddings, chunking, hybrid search, ranking, feedback loops), owning schema design, latency, and relevance across vector databases. LLM integration: Connect and orchestrate … AI development. Requirements: A motivated, hands-on engineer with an ownership mindset, strong communication skills, and a collaborative approach. 5+ years’ experience in full-stack development. Strong background in RAG systems , vector databases (pgvector, FAISS, Weaviate, Elasticsearch k-NN), embeddings, and hybrid search methods. Practical knowledge of chunking strategies, indexing, precision/recall trade-offs, reranking, and evaluation techniques. Proficient More ❯

BE DOING Build intelligent workflows using n8n, Microsoft Power Automate, Flowable, and similar tools. Design and implement agentic AI solutions, integrating LLMs and frameworks such as LangChain, AutoGen, and RAG pipelines with platforms like OpenAI. Collaborate with teams across the business to identify automation opportunities and enhance efficiency. Contribute to the company's AI and workflow automation architecture, ensuring scalability … Engineer - Essential Skills Hands-on experience with workflow automation tools such as n8n, Microsoft Power Automate, or Flowable. Strong understanding of LLM integration and agentic AI frameworks (LangChain, AutoGen, RAG). Proficiency in Python or JavaScript for scripting and workflow logic. Familiarity with APIs, event-driven architectures, and cloud platforms (Azure, AWS, or GCP). TO BE CONSIDERED Please either More ❯

Technical Leadership Define and lead the AI & Data Science vision and roadmap , aligned with business priorities. Provide technical oversight for AI initiatives across domains: Generative AI & LLMs (fine-tuning, RAG pipelines, multi-agent systems). Predictive Analytics & Time-Series Modeling . Computer Vision & Multimodal AI . Reinforcement Learning & Optimization . Knowledge Engineering & Semantic Search . Edge AI & Real-Time AI … and client engagements . Required Qualifications Significant experience in AI/ML, including experience in a technical leadership or team lead role . Strong knowledge (architectural & practical) of: LLMs, RAG, and AI Agents . Predictive analytics & time-series forecasting . Computer vision, multimodal learning, and geospatial AI . Reinforcement learning and optimization techniques . MLOps practices & data pipelines . Ability More ❯

Technical Leadership Define and lead the AI & Data Science vision and roadmap , aligned with business priorities. Provide technical oversight for AI initiatives across domains: Generative AI & LLMs (fine-tuning, RAG pipelines, multi-agent systems). Predictive Analytics & Time-Series Modeling . Computer Vision & Multimodal AI . Reinforcement Learning & Optimization . Knowledge Engineering & Semantic Search . Edge AI & Real-Time AI … and client engagements . Required Qualifications Significant experience in AI/ML, including experience in a technical leadership or team lead role . Strong knowledge (architectural & practical) of: LLMs, RAG, and AI Agents . Predictive analytics & time-series forecasting . Computer vision, multimodal learning, and geospatial AI . Reinforcement learning and optimization techniques . MLOps practices & data pipelines . Ability More ❯

ll Do Architecture & Development : Design and implement the cognitive systems that give AI agents consistent personalities, memory, and reasoning capabilities, using advanced LLM techniques like chain-of-thought prompting, RAG systems, and agentic tool use. Modeling & Experimentation : Design and run systematic experiments to evaluate agent behavior, test hypotheses about behavioral patterns, and iterate on model architectures based on empirical results … principles Experience working in fast-paced environments where requirements evolve rapidly Technical Skills LLM & Agent Development : Hands-on experience building applications with large language models, implementing advanced prompting techniques, RAG systems, and agentic workflows Backend Engineering : Proficient in Python and backend frameworks (e.g. FastAPI, Django, Flask); understanding of distributed systems and scalable architectures AI/ML Frameworks : Experience with PyTorch More ❯

ll Do Architecture & Development : Design and implement the cognitive systems that give AI agents consistent personalities, memory, and reasoning capabilities, using advanced LLM techniques like chain-of-thought prompting, RAG systems, and agentic tool use. Modeling & Experimentation : Design and run systematic experiments to evaluate agent behavior, test hypotheses about behavioral patterns, and iterate on model architectures based on empirical results … principles Experience working in fast-paced environments where requirements evolve rapidly Technical Skills LLM & Agent Development : Hands-on experience building applications with large language models, implementing advanced prompting techniques, RAG systems, and agentic workflows Backend Engineering : Proficient in Python and backend frameworks (e.g. FastAPI, Django, Flask); understanding of distributed systems and scalable architectures AI/ML Frameworks : Experience with PyTorch More ❯

ll Do Architecture & Development : Design and implement the cognitive systems that give AI agents consistent personalities, memory, and reasoning capabilities, using advanced LLM techniques like chain-of-thought prompting, RAG systems, and agentic tool use. Modeling & Experimentation : Design and run systematic experiments to evaluate agent behavior, test hypotheses about behavioral patterns, and iterate on model architectures based on empirical results … principles Experience working in fast-paced environments where requirements evolve rapidly Technical Skills LLM & Agent Development : Hands-on experience building applications with large language models, implementing advanced prompting techniques, RAG systems, and agentic workflows Backend Engineering : Proficient in Python and backend frameworks (e.g. FastAPI, Django, Flask); understanding of distributed systems and scalable architectures AI/ML Frameworks : Experience with PyTorch More ❯

directly on several key product enhancements. You’ll work with Python/Django, Javascript and AWS. Our platform is also increasingly AI-powered, so familiarity with implementing AI solutions (RAG etc) is an advantage. You’ll be working on a project where everything is hosted in AWS and we have a lightweight automated deployment process. You’ll work alongside a …/or ReactJS. Working understanding of data capture and performance tracking, a willingness to contribute to design and UX decisions. AI familiarity with working on Gen AI projects, including RAG and API integration. Ability to work within project timelines, proactively communicate any delays and contribute to task re-prioritisation to keep things on track Experience in developing websites, web applications More ❯

directly on several key product enhancements. You’ll work with Python/Django, Javascript and AWS. Our platform is also increasingly AI-powered, so familiarity with implementing AI solutions (RAG etc) is an advantage. You’ll be working on a project where everything is hosted in AWS and we have a lightweight automated deployment process. You’ll work alongside a …/or ReactJS. Working understanding of data capture and performance tracking, a willingness to contribute to design and UX decisions. AI familiarity with working on Gen AI projects, including RAG and API integration. Ability to work within project timelines, proactively communicate any delays and contribute to task re-prioritisation to keep things on track Experience in developing websites, web applications More ❯

directly on several key product enhancements. You’ll work with Python/Django, Javascript and AWS. Our platform is also increasingly AI-powered, so familiarity with implementing AI solutions (RAG etc) is an advantage. You’ll be working on a project where everything is hosted in AWS and we have a lightweight automated deployment process. You’ll work alongside a …/or ReactJS. Working understanding of data capture and performance tracking, a willingness to contribute to design and UX decisions. AI familiarity with working on Gen AI projects, including RAG and API integration. Ability to work within project timelines, proactively communicate any delays and contribute to task re-prioritisation to keep things on track Experience in developing websites, web applications More ❯

extraction, sentiment analysis, and qualitative insights Define reporting standards: Set quality bars for what makes a great dashboard (agent performance, app store trends, CSAT drivers, topic evolution, etc.) Optimize RAG pipelines: Design retrieval strategies and grounding approaches for report generation to ensure factual, relevant outputs Customer-Facing Analytics & Enablement (30%) Deliver bespoke insights: Partner with key … for accuracy and relevance, ensure quality before launch Operations & Optimization (10%) Monitor report health: Track delivery, engagement, and quality metrics; debug when outputs degrade Performance tuning: Optimize report generation costs and latency; balance API usage with quality Document everything: Maintain clear documentation for prompts, templates, and best practices What Makes You a Great FitTechnical Foundation 5+ years in … building customer insights, product analytics, or data-driven reporting AI-native experience: Hands-on work building reports or products using LLMs—prompt engineering, structured output generation, embeddings, RAG, summarization pipelines Python proficiency: Comfortable with pandas, OpenAI library, API integrations, and data manipulation for prototyping and analysis SQL fluency: Can write complex queries and understand data modeling Analytics tools More ❯

extraction, sentiment analysis, and qualitative insights Define reporting standards: Set quality bars for what makes a great dashboard (agent performance, app store trends, CSAT drivers, topic evolution, etc.) Optimize RAG pipelines: Design retrieval strategies and grounding approaches for report generation to ensure factual, relevant outputs Customer-Facing Analytics & Enablement (30%) Deliver bespoke insights: Partner with key … for accuracy and relevance, ensure quality before launch Operations & Optimization (10%) Monitor report health: Track delivery, engagement, and quality metrics; debug when outputs degrade Performance tuning: Optimize report generation costs and latency; balance API usage with quality Document everything: Maintain clear documentation for prompts, templates, and best practices What Makes You a Great FitTechnical Foundation 5+ years in … building customer insights, product analytics, or data-driven reporting AI-native experience: Hands-on work building reports or products using LLMs—prompt engineering, structured output generation, embeddings, RAG, summarization pipelines Python proficiency: Comfortable with pandas, OpenAI library, API integrations, and data manipulation for prototyping and analysis SQL fluency: Can write complex queries and understand data modeling Analytics tools More ❯

extraction, sentiment analysis, and qualitative insights Define reporting standards: Set quality bars for what makes a great dashboard (agent performance, app store trends, CSAT drivers, topic evolution, etc.) Optimize RAG pipelines: Design retrieval strategies and grounding approaches for report generation to ensure factual, relevant outputs Customer-Facing Analytics & Enablement (30%) Deliver bespoke insights: Partner with key … for accuracy and relevance, ensure quality before launch Operations & Optimization (10%) Monitor report health: Track delivery, engagement, and quality metrics; debug when outputs degrade Performance tuning: Optimize report generation costs and latency; balance API usage with quality Document everything: Maintain clear documentation for prompts, templates, and best practices What Makes You a Great FitTechnical Foundation 5+ years in … building customer insights, product analytics, or data-driven reporting AI-native experience: Hands-on work building reports or products using LLMs—prompt engineering, structured output generation, embeddings, RAG, summarization pipelines Python proficiency: Comfortable with pandas, OpenAI library, API integrations, and data manipulation for prototyping and analysis SQL fluency: Can write complex queries and understand data modeling Analytics tools More ❯

Python preferred; additional exposure to JavaScript/TypeScript or Go beneficial). Strong background in AI systems, cloud-native architectures, and modern ML tooling (LangChain, OpenAI API, vector stores, RAG pipelines). Experience designing distributed, high-availability platforms deployed on AWS or similar cloud environments. Excellent communication and stakeholder management skills, with the ability to translate technical direction into business … to the property, SaaS, or workflow automation space is advantageous. Summary A rare opportunity for a technically strong, execution-focused engineering leader to shape and scale a next-generation AI automation platform from the ground up — with full ownership of the engineering strategy, team, and architecture. More ❯

Python preferred; additional exposure to JavaScript/TypeScript or Go beneficial). Strong background in AI systems, cloud-native architectures, and modern ML tooling (LangChain, OpenAI API, vector stores, RAG pipelines). Experience designing distributed, high-availability platforms deployed on AWS or similar cloud environments. Excellent communication and stakeholder management skills, with the ability to translate technical direction into business … to the property, SaaS, or workflow automation space is advantageous. Summary A rare opportunity for a technically strong, execution-focused engineering leader to shape and scale a next-generation AI automation platform from the ground up — with full ownership of the engineering strategy, team, and architecture. More ❯

doing: • Owning the design and build of LLM-based systems end-to-end • Fine-tuning and adapting models (LoRA, instruction tuning, PEFT etc) rather than just prompt-engineering • Building RAG workflows, embedding strategies, memory layers and domain grounding • Working out how to measure output quality, reduce hallucination risk and improve robustness • Optimising inference performance (quantisation, distillation, pruning, batching, caching) • Deploying … prototyping/notebooks • Strong Python and experience with PyTorch/Hugging Face/similar tooling • Experience deploying models into production (not just training them) • Familiarity with vector stores and RAG patterns • Comfortable operating in a hybrid environment and speaking with stakeholders where required • Someone who enjoys solving real problems end-to-end: from understanding the domain → designing the approach → shipping More ❯

doing: • Owning the design and build of LLM-based systems end-to-end • Fine-tuning and adapting models (LoRA, instruction tuning, PEFT etc) rather than just prompt-engineering • Building RAG workflows, embedding strategies, memory layers and domain grounding • Working out how to measure output quality, reduce hallucination risk and improve robustness • Optimising inference performance (quantisation, distillation, pruning, batching, caching) • Deploying … prototyping/notebooks • Strong Python and experience with PyTorch/Hugging Face/similar tooling • Experience deploying models into production (not just training them) • Familiarity with vector stores and RAG patterns • Comfortable operating in a hybrid environment and speaking with stakeholders where required • Someone who enjoys solving real problems end-to-end: from understanding the domain → designing the approach → shipping More ❯

doing: • Owning the design and build of LLM-based systems end-to-end • Fine-tuning and adapting models (LoRA, instruction tuning, PEFT etc) rather than just prompt-engineering • Building RAG workflows, embedding strategies, memory layers and domain grounding • Working out how to measure output quality, reduce hallucination risk and improve robustness • Optimising inference performance (quantisation, distillation, pruning, batching, caching) • Deploying … prototyping/notebooks • Strong Python and experience with PyTorch/Hugging Face/similar tooling • Experience deploying models into production (not just training them) • Familiarity with vector stores and RAG patterns • Comfortable operating in a hybrid environment and speaking with stakeholders where required • Someone who enjoys solving real problems end-to-end: from understanding the domain → designing the approach → shipping More ❯

Are you an AI engineer with strong software engineering fundamentals? Have you deployed AI models into production—not just trained them? Want to work on agentic systems, RAG pipelines, and LLM-powered tools? We're working with a high-growth GenAI consultancy building real-world, production-grade AI applications. With a team of 50+, the company partners with global clients … deployment, collaborating with cross-functional teams and mentoring other engineers. Key Responsibilities Build and deploy scalable AI tools using Python and LLM APIs Design end-to-end agentic and RAG-based solutions for enterprise use Own delivery from proof-of-concept through to production Work with cloud-native architectures (e.g. AWS Lambda, Step Functions) Lead and guide junior engineers within More ❯

Are you an AI engineer with strong software engineering fundamentals? Have you deployed AI models into production—not just trained them? Want to work on agentic systems, RAG pipelines, and LLM-powered tools? We're working with a high-growth GenAI consultancy building real-world, production-grade AI applications. With a team of 50+, the company partners with global clients … deployment, collaborating with cross-functional teams and mentoring other engineers. Key Responsibilities Build and deploy scalable AI tools using Python and LLM APIs Design end-to-end agentic and RAG-based solutions for enterprise use Own delivery from proof-of-concept through to production Work with cloud-native architectures (e.g. AWS Lambda, Step Functions) Lead and guide junior engineers within More ❯

Are you an AI engineer with strong software engineering fundamentals? Have you deployed AI models into production—not just trained them? Want to work on agentic systems, RAG pipelines, and LLM-powered tools? We're working with a high-growth GenAI consultancy building real-world, production-grade AI applications. With a team of 50+, the company partners with global clients … deployment, collaborating with cross-functional teams and mentoring other engineers. Key Responsibilities Build and deploy scalable AI tools using Python and LLM APIs Design end-to-end agentic and RAG-based solutions for enterprise use Own delivery from proof-of-concept through to production Work with cloud-native architectures (e.g. AWS Lambda, Step Functions) Lead and guide junior engineers within More ❯

Do you want to build the infrastructure powering the next generation of AI agents? Have you scaled backend systems that drive automation at speed? Ready to join a profitable AI startup transforming how industries deploy technology? A profitable, fast-growing AI company is building the “roads” for AI agents — providing the infrastructure that lets businesses deploy and integrate …/LLM components into production systems. Role Breakdown: 50% Backend Engineering: FastAPI, Flask, Node.js, CI/CD 30% Data Engineering: ETL, DBT, Airflow 20% AI/LLM Integration: LangChain, RAG pipelines, orchestration Key Responsibilities: Design and build backend services to support AI agent deployment Develop scalable data pipelines and integration layers Implement AI/LLM-powered features with LangChain and … of Front-End, and adoption engineers Reporting Line: CTO Visa: Cannot sponsor Ideal Profile: 5–8 years’ experience in backend or data engineering (Python) Exposure to AI/LLMs, RAG, or personal AI side projects Experience in startups or scale-ups where you’ve helped build or grow systems Solid education and strong coding fundamentals Comfortable working in a small More ❯

Do you want to build the infrastructure powering the next generation of AI agents? Have you scaled backend systems that drive automation at speed? Ready to join a profitable AI startup transforming how industries deploy technology? A profitable, fast-growing AI company is building the “roads” for AI agents — providing the infrastructure that lets businesses deploy and integrate …/LLM components into production systems. Role Breakdown: 50% Backend Engineering: FastAPI, Flask, Node.js, CI/CD 30% Data Engineering: ETL, DBT, Airflow 20% AI/LLM Integration: LangChain, RAG pipelines, orchestration Key Responsibilities: Design and build backend services to support AI agent deployment Develop scalable data pipelines and integration layers Implement AI/LLM-powered features with LangChain and … of Front-End, and adoption engineers Reporting Line: CTO Visa: Cannot sponsor Ideal Profile: 5–8 years’ experience in backend or data engineering (Python) Exposure to AI/LLMs, RAG, or personal AI side projects Experience in startups or scale-ups where you’ve helped build or grow systems Solid education and strong coding fundamentals Comfortable working in a small More ❯

Do you want to build the infrastructure powering the next generation of AI agents? Have you scaled backend systems that drive automation at speed? Ready to join a profitable AI startup transforming how industries deploy technology? A profitable, fast-growing AI company is building the “roads” for AI agents — providing the infrastructure that lets businesses deploy and integrate …/LLM components into production systems. Role Breakdown: 50% Backend Engineering: FastAPI, Flask, Node.js, CI/CD 30% Data Engineering: ETL, DBT, Airflow 20% AI/LLM Integration: LangChain, RAG pipelines, orchestration Key Responsibilities: Design and build backend services to support AI agent deployment Develop scalable data pipelines and integration layers Implement AI/LLM-powered features with LangChain and … of Front-End, and adoption engineers Reporting Line: CTO Visa: Cannot sponsor Ideal Profile: 5–8 years’ experience in backend or data engineering (Python) Exposure to AI/LLMs, RAG, or personal AI side projects Experience in startups or scale-ups where you’ve helped build or grow systems Solid education and strong coding fundamentals Comfortable working in a small More ❯