Keytag.ai is looking for a skilled Python Developer with expertise in Neo4j and Cypher to join our growing team. Youll be working on enhancing existing products and contributing to all stages of the development lifecycle from design and implementation to deployment and support. This is a great opportunity to work in a dynamic, startup-style environment with the security of long-term customer contracts already in place. Core Skills Required Strong Python development skills, particularly in designing and building FastAPI web services Hands-on experience with Neo4j and the Cypher query language Proficient with Docker, Git, and CI/CD pipelines Solid experience in data engineering, including use of pandas and other data science libraries Comfortable working in a Linux environment using VSCode and GitHub A proactive, self-starting attitude with a passion for learning, problem-solving, and contributing ideas to both design and development Desirable (but not required you’ll gain experience here) Experience with Apache Airflow (designing and troubleshooting DAGs) Familiarity with Redis (used for caching and vector storage) What You’ll Be Working On Extend and enhance existing products, including: A knowledge-graph-based intelligence system for a pharmaceutical client Data lineage and discovery tools Multiple agent-based systems powered by large language models (LLMs) Design, build, and maintain APIs using FastAPI Model and optimize complex data relationships in Neo4j; manage related caching with Redis Collaborate closely with frontend developers, architects, and data experts to deliver new features Contribute to overall system architecture, performance tuning, and security enhancements Participate in daily team standups, work closely on shared tasks, and engage directly with clients to discuss requirements, troubleshoot, and deliver solutions Benefits Remote work opportunity, providing flexibility and work-life balance. Medical insurance coverage for you and your family. Join a friendly and well-organized team with an open communication style. Continuous opportunities to grow your technical and soft skills.
Keytag.ai is looking for a talented React Developer to join our product team. Youll work on high-impact web applications that integrate with intelligent backend systems including knowledge graphs, LLM agents, and complex data pipelines. This role is ideal for someone who enjoys building user-friendly, performant interfaces and wants to have a say in product design and direction all within a stable environment backed by long-term customer contracts. Core Skills Required Strong experience building applications with React (Hooks, Context, Components) Familiarity with manipulating json data from webservices. Solid understanding of state management, component design, and UI/UX best practices Comfortable using Git, CI/CD pipelines, and Docker for frontend deployment Ability to develop in a Linux environment, using VSCode and GitHub A self-starter who enjoys solving problems, collaborating with others, and influencing product design Desirable Experience with gojs, ag-grid frameworks. Experience designing for AI Assistants, knowledge graphs, or data-driven applications Experience developing applications in Angular. What Youll Be Working On Build and improve UI components and features for: A knowledge-graph-powered intelligence dashboard for a pharma client Tools for tracking and visualising data lineage and discovery Frontends for LLM-powered agent systems and smart applications Collaborate closely with backend developers, architects, and data teams to shape user-facing features Contribute to design discussions and help shape our user experience and frontend architecture Participate in daily standups, shared team tasks, and direct communication with customers for feature feedback and troubleshooting Benefits Remote work opportunity, providing flexibility and work-life balance. Medical insurance coverage for you and your family. Join a friendly and well-organized team with an open communication style. Continuous opportunities to grow your technical and soft skills.
Keytag.ai are looking for AI/LLM engineers with to join our team building a new global LLM operations and agent framework for a large pharmaceutical organization. We are rolling out an eco-system of LLM Agents to generate documents, to automate workflows, and to perform new tasks across the organization. We are using cloud hosted and on-prem models as appropriate to the business area, and combining RAG, fine-tuning and some training. This a great opportunity to work with all aspects of Generative AI, in a startup mode with the security of company that has fixed customer contracts for the coming years. Core Skills Required Experienced in developing RAG based LLM solutions, handling all aspects from document splitting and chunking strategies, domain specific retrieval strategies, prompt development, performance tuning and production troubleshooting. Good understanding of LangChain and LangGraph libraries. Strong Python development and code design skills. Experienced in all aspects of data engineering and operations Ability to develop in Linux Environment, VSCode, github. Self starter keen to learn, enjoys delivering solutions, happy to give opinions and influence the design as well as the development of solutions. Additional Desirable Skills : Development of domain specific and/or task specific Agents in langgraph or another library. Experience designing and developing multi-agent flows. Experience with Langfuse, DeepEval or DPSy Fine-Tuning of models (and sample generation) to understand an organizations vernacular and services. Experience with multiple model providers eg Openai, Azure Openai, Lllama, Falcon. Experience using Neo4j, Redis, Fastapi, Airflow. What the role will involve : Working with the business on specific use cases to develop Agents to perform specific tasks and fit within our existing agent framework. Use cases are a variety of question answering and summarization, document and asset generation, workflow automation, and brand new tasks to replace complex human analysis. Enhancing our agent framework and ecosystem as requirements change and Gen AI technology advances. Creating a suite of models that can be used by the business; fine-tuned organization LLM and smaller task/domain specific llms. Using both cloud and on-prem open source models as appropriate. Enhancing our MLOps practices and improving our testing automations Sourcing and mapping data from a wide range of services including neo4j and relational databases, SAAS services, security and general business document stores. It is a remote role but there is plenty of interaction with the rest of the team, with daily standups and shared tasks, as well as directly working with customers on projects to discuss changes, implement, troubleshoot solutions etc. Benefits Remote work opportunity, providing flexibility and work-life balance. Medical insurance coverage for you and your family. Join a friendly and well-organized team with an open communication style. Continuous opportunities to grow your technical and soft skills.
Keytag.ai is seeking a DevOps / Platform Engineer with strong Kubernetes experience to help us evolve our product deployment model. We're transitioning to a platform engineering approach for delivering and maintaining intelligent, data-driven applications across customer environments. Youll play a critical role in re-architecting our infrastructure, transforming our CI/CD pipelines, and enabling robust, scalable deployments. This a great opportunity to work in a startup mode with the security of company that has fixed customer contracts for the coming years. Core Skills Required Experience architecting and deploying applications with Kubernetes Strong Python skills for understanding our code as well as scripting automations. Experience designing and maintaining CI/CD pipelines Strong understanding of platform observability, security, and infrastructure-as-code practices Desirable Experience with OpenShift Exposure to data-centric applications (Neo4j, Redis, or AI/LLM systems) What Youll Be Working On Lead the migration of our product stack to a platform engineering model, enabling consistent customer deployments Transform and modernize our CI/CD pipelines for speed, reliability, and traceability Collaborate with development teams to improve application packaging, infrastructure, and deployment flows Build tooling and automation to streamline internal workflows and customer onboarding Enhance deployment security, observability, and self-service capabilities Engage in daily standups, collaborate with developers and architects, and work directly with customers on implementation and troubleshooting Benefits Remote work opportunity, providing flexibility and work-life balance. Medical insurance coverage for you and your family. Join a friendly and well-organized team with an open communication style. Continuous opportunities to grow your technical and soft skills.
Keytag.ai is seeking a DevOps / Platform Engineer with strong Kubernetes experience to help us evolve our product deployment model. We're transitioning to a platform engineering approach for delivering and maintaining intelligent, data-driven applications across customer environments. Youll play a critical role in re-architecting our infrastructure, transforming our CI/CD pipelines, and enabling robust, scalable deployments. This a great opportunity to work in a startup mode with the security of company that has fixed customer contracts for the coming years. Core Skills Required Experience architecting and deploying applications with Kubernetes. Strong Python skills for understanding our code as well as scripting automations. Experience designing and maintaining CI/CD pipelines Strong understanding of platform observability, security, and infrastructure-as-code practices Desirable Experience with OpenShift Exposure to data-centric applications (Neo4j, Redis, or AI/LLM systems) What You Will Be Working On Lead the migration of our product stack to a platform engineering model, enabling consistent customer deployments Transform and modernize our CI/CD pipelines for speed, reliability, and traceability Collaborate with development teams to improve application packaging, infrastructure, and deployment flows Build tooling and automation to streamline internal workflows and customer onboarding Enhance deployment security, observability, and self-service capabilities Engage in daily standups, collaborate with developers and architects, and work directly with customers on implementation and troubleshooting Benefits Remote work opportunity, providing flexibility and work-life balance. Medical insurance coverage for you and your family. Join a friendly and well-organized team with an open communication style. Continuous opportunities to grow your technical and soft skills.
Knowledge Graph Engineer Keytag.ai is seeking a Knowledge Graph Engineer to help us design and deliver a new generation of organisational knowledge systems for a major global pharmaceutical organisation. You will play a central role in modelling business knowledge, extracting structured meaning from documents, and implementing scalable graph-based solutions across cloud and on-prem environments. This is an opportunity to work at the forefront of enterprise AI and knowledge engineeringcombining semantic modelling, retrieval architectures, and operational tooling—in a start-up environment backed by long-term customer contracts. Core Responsibilities Design and develop knowledge graphs that represent organisational processes, structured data, unstructured content, and domain-specific relationships. Model data extracted from documents (procedures, regulatory texts, SOPs, scientific materials, business documents, etc.) into consistent ontologies and graph schemas. Implement graph solutions in Neo4j , including data modelling, Cypher queries, indexing strategies, and performance tuning. Build data ingestion and transformation pipelines using Python, Airflow, and modern ETL/ELT patterns. Work with AI/ML and RAG teams to enable graph-enhanced retrieval , semantic search, and grounding for LLM-based agents. Collaborate with business stakeholders to understand use cases and convert them into scalable graph designs. Contribute to evolving our data and MLOps ecosystem, including testing, evaluation, and automation improvements. Required Skills Proven experience designing organisational knowledge graphs , taxonomies, schema/ontology definitions, and domain models. Strong understanding of graph theory , semantic modelling, and representing complex relationships. Hands-on experience with Neo4j (data modelling, Cypher, performance optimisation, and graph integration patterns). Solid Python development skills , including data processing, pipeline development, and interaction with Neo4j and related services. Experience working with both structured and unstructured data sources (documents, databases, SaaS systems). Ability to work independently, think critically, and collaborate in a fast-moving team. Desirable Skills Experience in the pharmaceutical domain , including regulatory processes, clinical data, R&D, or quality operations. Familiarity with Graph RAG , knowledge-grounded LLMs, or hybrid retrieval architectures. Benefits Remote work opportunity, providing flexibility and work-life balance. Medical insurance coverage for you and your family. Join a friendly and well-organized team with an open communication style. Continuous opportunities to grow your technical and soft skills.
Keytag.ai is looking for AI/ML Engineers with to join our team building a new global LLM operations and agent framework for a large pharmaceutical organisation. We are rolling out an eco-system of LLM Agents to generate documents, automate workflows, and to perform new tasks across the organisation. We are using cloud hosted and on-prem models as appropriate to the business area, and combining hybrid retrieval methods, fine-tuning and training. This is a great opportunity to work with all aspects of Generative AI, in a startup mode with the security of a company that has fixed customer contracts for the coming years. Core Skills Required Demonstrable experience in the development of domain specific and/or task specific Agents in LangGraph. Experienced in developing RAG based LLM solutions, handling all aspects from document splitting and chunking strategies, domain specific retrieval strategies, prompt development, performance tuning and production troubleshooting. Comprehensive understanding of LangChain and LangGraph libraries, including swarm and deep agent architectures. Strong Python development and code design skills. Experience in building FastAPI based api services. Experienced in all aspects of data engineering and building scalable products. Self starter keen to learn, enjoys delivering solutions, and is happy to give opinions and influence the design as well as the development of solutions. Additional Desirable Skills : Understanding of the importantance of evaluation led development. Experience designing and developing multi-agent flows. Experience with Langfuse, DeepEval or DSPY. Fine-Tuning of models (and sample generation) to understand an organisation's vernacular and services. Actual experience with Graph RAG and similar retrieval / grounding methods. Experience with multiple model providers eg OpenAI, Azure Openai, Claude, GPT-OSS, Deepseek. Experience using Neo4j, Redis, Fastapi, Airflow. What the role will involve : Working with the business on specific use cases to develop Agents to perform specific tasks and fit within our existing agent framework. Use cases are a variety of question answering and summarization, document and asset generation, workflow automation, and brand new tasks to replace complex human analysis. Enhancing our agent framework and ecosystem as requirements change and Gen AI technology advances. Creating a suite of models that can be used by the business; fine-tuned organisational LLM and smaller task/domain specific LLMs. Using both cloud and on-prem open source models as appropriate. Enhancing our MLOps practices and improving our testing and eval automations Sourcing and mapping data from a wide range of services including neo4j and relational databases, SaaS services, security and general business document stores. It is a remote role but there is plenty of interaction with the rest of the team, with daily standups and shared tasks, as well as directly working with customers on projects to discuss changes, design and troubleshoot solutions, etc. Benefits Remote work opportunity, providing flexibility and work-life balance. Medical insurance coverage for you and your family. Join a friendly and well-organized team with an open communication style. Continuous opportunities to grow your technical and soft skills.
Keytag.ai is looking for AI/ML Engineers with to join our team building a new global LLM operations and agent framework for a large pharmaceutical organisation. We are rolling out an eco-system of LLM Agents to generate documents, automate workflows, and to perform new tasks across the organisation. We are using cloud hosted and on-prem models as appropriate to the business area, and combining hybrid retrieval methods, fine-tuning and training. This is a great opportunity to work with all aspects of Generative AI, in a startup mode with the security of a company that has fixed customer contracts for the coming years. Core Skills Required Demonstrable experience in the development of domain specific and/or task specific Agents in LangGraph. Experienced in developing RAG based LLM solutions, handling all aspects from document splitting and chunking strategies, domain specific retrieval strategies, prompt development, performance tuning and production troubleshooting. Comprehensive understanding of LangChain and LangGraph libraries, including swarm and deep agent architectures. Strong Python development and code design skills. Experience in building FastAPI based api services. Experienced in all aspects of data engineering and building scalable products. Self starter keen to learn, enjoys delivering solutions, and is happy to give opinions and influence the design as well as the development of solutions. Additional Desirable Skills : Understanding of the importantance of evaluation led development. Experience designing and developing multi-agent flows. Experience with Langfuse, DeepEval or DSPY. Fine-Tuning of models (and sample generation) to understand an organisation's vernacular and services. Actual experience with Graph RAG and similar retrieval / grounding methods. Experience with multiple model providers eg OpenAI, Azure Openai, Claude, GPT-OSS, Deepseek. Experience using Neo4j, Redis, Fastapi, Airflow. What the role will involve : Working with the business on specific use cases to develop Agents to perform specific tasks and fit within our existing agent framework. Use cases are a variety of question answering and summarization, document and asset generation, workflow automation, and brand new tasks to replace complex human analysis. Enhancing our agent framework and ecosystem as requirements change and Gen AI technology advances. Creating a suite of models that can be used by the business; fine-tuned organisational LLM and smaller task/domain specific LLMs. Using both cloud and on-prem open source models as appropriate. Enhancing our MLOps practices and improving our testing and eval automations Sourcing and mapping data from a wide range of services including neo4j and relational databases, SaaS services, security and general business document stores. It is a remote role but there is plenty of interaction with the rest of the team, with daily standups and shared tasks, as well as directly working with customers on projects to discuss changes, design and troubleshoot solutions, etc. Benefits Remote work opportunity, providing flexibility and work-life balance. Medical insurance coverage for you and your family. Join a friendly and well-organized team with an open communication style. Continuous opportunities to grow your technical and soft skills.