Robson Bale Ltd

Senior AI Engineer - Permanent - London/Hybrid Permanent Hybrid in Central London Competitive Salary Key Responsibilities Technical Design & Delivery Contribute to the technical design and architecture of scalable AI solutions. Evaluate AI technologies, frameworks, and third-party services, making recommendations based on technical and business requirements. Participate in technical design reviews and support architectural decisions for complex AI initiatives. Help implement responsible AI, model governance, and production machine learning practices. Work with technical and product stakeholders to translate business requirements into practical AI solutions. Provide technical insights and feasibility assessments to support product and engineering decisions. Technical Expertise & Execution Solve complex AI engineering challenges and provide technical guidance to other engineers. Develop proof-of-concepts for emerging AI technologies and assess their suitability for production use. Build and deliver production-ready AI and Generative AI solutions using LLMs, RAG architectures, agents, and responsible AI practices. Implement and maintain retrieval pipelines using embeddings, vector databases, hybrid search methods, and effective chunking strategies. Design evaluation approaches to assess model quality, retrieval performance, reliability, and business outcomes. Use AI coding assistants such as Cursor, GitHub Copilot, and Claude Code to accelerate development while maintaining ownership of code quality and outcomes. Diagnose and resolve performance, scalability, reliability, and cost issues within production AI systems. Engineering Standards & Enablement Contribute to engineering best practices, coding standards, and quality benchmarks for AI development. Develop and improve internal AI tooling, including shared libraries, SDKs, and reusable components for RAG, tracing, prompt management, and evaluation. Conduct code reviews and support the development of less-experienced engineers through mentoring and knowledge sharing. Contribute to internal AI enablement activities, technical documentation, demonstrations, and best-practice guidance. Promote maintainable, observable, secure, and well-tested approaches to AI engineering. Cross-functional Collaboration Collaborate closely with Product using a working-backwards approach, contributing to technical designs, breaking down work, and delivering iteratively. Work with Security, Legal, and Data teams to apply AI policies and address privacy, PII protection, security, and regulatory requirements. Communicate technical decisions, risks, trade-offs, and progress clearly to technical and non-technical stakeholders. Partner with software, platform, and data engineers to integrate AI capabilities into wider products and services. Skills, Knowledge and Expertise Must Have 5+ years of software engineering experience, including 2+ years building production AI, Generative AI, or RAG systems. Strong experience designing, building, deploying, and maintaining AI systems in production environments. Demonstrated ability to make sound technical decisions and deliver solutions with measurable business impact. Strong knowledge of LLMs, RAG, agentic workflows, prompt engineering, embeddings, vector databases, and hybrid search techniques. Hands-on experience with leading LLM providers, such as Anthropic and OpenAI, including model selection, evaluation, and optimisation. Advanced Python development skills and experience using AI coding assistants such as Cursor, GitHub Copilot, or Claude Code. Production experience with AWS cloud services and containerised environments, including Kubernetes. Experience building reliable APIs, services, and integration patterns for AI-enabled applications. Strong data engineering capabilities, including dataset creation, ETL development, data quality management, and metrics definition. Solid understanding of machine learning fundamentals, experimentation methodologies, and model performance optimisation. Strong technical communication skills and the ability to collaborate effectively across engineering, product, data, security, and legal teams. Experience applying software engineering practices such as automated testing, version control, continuous integration, observability, and documentation. Nice to Have Experience with model fine-tuning, RLHF, or custom training approaches. Familiarity with MLOps platforms and experiment-tracking tools. Experience with infrastructure as code, such as Terraform or CloudFormation. Experience with LLM evaluation, tracing, prompt management, or AI observability platforms. Background in NLP research or contributions to open-source AI or machine learning projects.

We're looking for an experienced Python Engineer to join a newly formed team working alongside a client's Product Owner, Technical Lead, and development team. You'll design, build, and optimize scalable, cloud-based data pipelines and ensure top performance in production environments. Key Responsibilities: Develop and maintain data ingestion and ETL pipelines using Python and tools like Airflow, Dagster, or Prefect Design asynchronous workflows and event-driven architectures with Kafka, RabbitMQ, or similar Optimize performance and reliability of large-scale data systems Automate and monitor data workflows for scalability and observability Collaborate with business and product teams to deliver robust, compliant data solutions Requirements: 6+ years of Python development experience focused on data pipelines Expertise with SQL/NoSQL, Airflow/Dagster/Prefect, and message brokers Hands-on experience with Docker, Kubernetes, and AWS/GCP/Azure Strong knowledge of OOP and Agile practices Excellent communication and problem-solving skills Experience in real estate or mortgage data (preferred) Familiarity with ML integration and data privacy/compliance (a plus)

Consultant - Securities Subject Matter Expert - Contract - Hybrid/London - £860pd Inside IR35 12 month contract £860pd Inside IR35 1 day per week on site Job Description An experienced individual with deep knowledge and proven expertise working within or closely with a Central Securities Depository (CSD). The successful candidate will provide critical subject matter expertise on Bonds and UK Gilts life cycle to inform the design and development of a Digital Securities Depository (DSD). In this role, the individual will contribute domain expertise to support product design, regulatory engagement, and market outreach, helping ensure the DSD is aligned with market expectations, regulatory frameworks, and operational realities. This is a unique opportunity to help shape the future of the UK's financial market infrastructure from the ground up-without requiring prior experience in digital assets or blockchain. Role Responsibilities Provide subject matter expertise on the full life cycle of Bonds and UK gilts (issuance, settlement, custody, corporate actions) to inform the design of a fit-for-purpose Digital Securities Depository. Work closely with internal product, technology, and legal teams to translate traditional CSD services into digital equivalents while ensuring regulatory, operational, and market continuity. Collaborate on the definition of the target operating model for the DSD, including participant roles, post-trade workflows, and asset servicing processes. Support in discussions with key stakeholders in the ecosystem to validate assumptions and refine the solution and product roadmap.

Product Manager - Clear Derivatives (OTC & ETD) - Contract - London/Hybrid - £520pd Inside IR35 Location: Central London (3 days on-site) Duration: 6 months initially Rate: £520/day (Inside IR35) Overview Seeking an experienced Product Manager with strong knowledge of OTC and ETD derivatives to lead product initiatives within a regulated financial environment. The role bridges stakeholders and technology teams, ensuring delivery of high-value projects in line with business goals. Key Responsibilities Drive product planning, delivery, and life cycle management in an Agile framework. Act as the link between business, technology, and external partners. Produce and manage documentation (requirements, specifications, roadmaps). Manage risks, priorities, and deadlines effectively. Communicate clearly with technical and non-technical stakeholders. Requirements Proven Product Management experience in financial services (OTC & ETD). Strong knowledge of Agile (Scrum/Kanban). Excellent stakeholder management and communication skills. Experience producing and managing project documentation. Strong risk and time management in regulated environments.