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Goto Ventures is an innovative technology and consulting business specialising in Generative AI, Internet of Things, Utilities, and Financial Services. With a track record of delivering transformational technology across complex, regulated industries, Goto Ventures is now accelerating its AI ambitions — building next-generation platforms that bring the power of agentic and generative AI directly into trading floors, energy desks and wealth management operations.

We are investing significantly in our AI-driven platform capabilities across three high-growth verticals: financial services trading and risk management, energy trading and Net Zero advisory, and wealth management. This role sits at the heart of that build-out, combining deep software engineering with cloud infrastructure expertise to deliver the platforms our clients depend on.

The AI Infrastructure Development Engineer will be a core contributor to the design, build and evolution of Goto Ventures’ AI-driven trading and risk management platforms. Working within the Tech Delivery organisation on a growing AWS cloud footprint, you will be responsible for engineering the infrastructure and platform components that underpin real-time AI workloads across financial services, energy trading and wealth management sectors.

This is a software engineering-led infrastructure role. You will write production-quality code to build and automate cloud infrastructure, develop platform services, and integrate AI capabilities into mission-critical systems. You will collaborate directly with quants, trading technologists, data scientists and domain SMEs to translate complex financial and energy domain requirements into robust, scalable platform solutions.

Salary - £51,000 per annum

Full-time and hybrid working

Glasgow and Manchester Office/Client locations

Key Responsibilities

• Design, build and operate cloud-native infrastructure on AWS to support AI-driven trading, risk management and wealth management platforms.
• Develop platform services and APIs that expose AI and ML capabilities (including generative and agentic AI) to trading, risk and advisory applications.
• Implement real-time and near-real-time data pipelines to feed AI models with market data, portfolio positions, risk signals and energy trading feeds.
• Integrate large language models (LLMs) and agentic AI frameworks into platform workflows, supporting use cases such as automated risk commentary, trade surveillance and Net Zero advisory agents.
• Build and maintain model serving infrastructure, ensuring low-latency, high-availability inference for time-sensitive trading and risk workloads.

• Collaborate with quantitative analysts, risk managers and trading technologists to understand domain requirements and translate them into reliable platform components.
• Develop platform capabilities specific to financial services trading and risk management, including position management, P&L attribution and regulatory reporting infrastructure.
• Build infrastructure to support energy trading operations, including real-time pricing feeds, capacity management and Net Zero compliance analytics.
• Deliver platform components for wealth management use cases, such as portfolio analytics, client reporting automation and AI-assisted advisory tools.
• Ensure all platforms meet the regulatory, security and audit requirements of the financial services and energy trading sectors (e.g. FCA, MiFID II, REMIT, EMIR).

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Mathematics, Physics or a related quantitative discipline, or equivalent industry experience.
• 10+ years of experience in platform engineering, cloud infrastructure development or software engineering roles, with a focus on production AI or financial systems.
• Demonstrable passion for AI, cloud-native engineering and the application of advanced technology within financial and energy markets.

• Strong proficiency in at least one high-level programming language used in financial and AI platform engineering (Python, Java, Go, C++ or TypeScript).
• Proven experience building production-quality cloud infrastructure and platform services on AWS.
• Deep hands-on expertise with Infrastructure as Code (Terraform and/or AWS CDK/CloudFormation), including module design, testing and CI/CD integration.
• Experience designing and implementing RESTful or event-driven APIs for platform service integration.
• Solid understanding of distributed systems, microservices architecture and event streaming (Kafka, AWS Kinesis or equivalent).

• Demonstrable experience building infrastructure for AI or ML workloads, including model serving, feature stores or real-time inference pipelines.
• Familiarity with AWS AI/ML services (SageMaker, Bedrock, Lambda for inference) and open-source ML frameworks (PyTorch, TensorFlow, Hugging Face).
• Understanding of agentic AI frameworks and LLM integration patterns, including prompt engineering, RAG architectures and tool-use patterns.
• Experience integrating AI models into production systems with appropriate monitoring, versioning and drift detection.

Responsibilities: 

• This is a software engineering-led infrastructure role. You will be expected to author production-quality code to establish and automate cloud infrastructure, develop platform services, and seamlessly integrate AI capabilities into our mission-critical systems.
• Creation of solution designs and proposals whilst working closely with the sales teams when scoping out solutions and estimates for new projects.
• Implementation and maintenance of all cloud infrastructure using an Infrastructure as Code approach (such as Terraform, AWS CDK or CloudFormation), ensuring reproducibility, peer review and version control.
• Design and management of scalable, secure, multi-environment AWS architectures appropriate for regulated financial and energy workloads.
• Driving automation across the platform build and deployment lifecycle, minimising manual intervention and maximising reliability.
• Ownership of the quality of infrastructure code through automated testing, static analysis, policy-as-code and security scanning integrated into CI/CD pipelines.
• Provide post implementation support and changes where required by customers.
• Coordinate work with external design consultants, contractors and specialists, supervise installation of 3rd party teams.