Top Python Jobs in London

The Quantitative Strategist will develop and optimize systems for treasury functions, including pricing, allocation, and profitability frameworks, while collaborting with technology and business partners.

The Rapid Application Developer will utilize rapid development techniques for projects, build trading frameworks, support applications, and manage data systems.

The Solutions Engineer will drive technical success with Algolia's solutions, partner with sales, demonstrate product capabilities, and advocate customer needs internally, ensuring customer satisfaction and onboarding success.

The Senior Solutions Engineer at Algolia works with sales and customers to drive technical success, demonstrating product capabilities and developing custom search applications while contributing to product feedback and customer advocacy.

Seeking a fullstack software engineer to design and build AI-driven agent systems, focusing on scalable solutions and backend integration. Responsibilities include collaborating with cross-functional teams and ensuring reliability of components.

As an AI Engineer, you will architect, develop, and deploy scalable AI applications, collaborating with teams to implement AI solutions that drive enterprise productivity and innovation.

As Director of Product Engineering, you will oversee product squads, ensuring engineering excellence, managing architectural roadmaps, and collaborating with cross-functional teams to deliver data-driven solutions while maintaining compliance.

The Senior Product Engineer will develop technical plans, write Ruby code, mentor engineers, and collaborate with product teams to enhance customer service solutions.

The Principal Solutions Engineer guides solution design for integration technologies, supports sales activities, and delivers high-quality presentations and workshops to showcase SimCorp solutions.

The Reinsurance Pricing Actuary will support QBE Re's pricing strategy and methodologies, collaborating with stakeholders to enhance models, ensure compliance, and drive profitable growth. Responsibilities include developing pricing tools, analyzing data, and mentoring team members.

Lead technical customer engagements to design and implement full-stack solutions using Retool. Build Retool applications, integrate enterprise systems, enable partners, scope and deliver professional services, and provide technical guidance and risk management to ensure scalable, production-grade internal tools.

Serve as the Data Science Director's right hand to prioritise work, remove blockers, run model monitoring and change control, coordinate deployments, manage cross-team dependencies, run hiring and onboarding, and prepare decision-ready materials for senior stakeholders to ensure disciplined, fast delivery of credit and decisioning models.

Bridge patent practice and AI product development: engineer LLM outputs for patent tasks, build legal benchmarks and datasets, drive product roadmap, run pilots with global IP teams, and document AI adoption playbooks.

Design and maintain multi-region AWS infrastructure with Terraform, build isolated single-tenant environments, architect CI/CD (GitHub Actions, Docker), implement observability (OpenTelemetry, Datadog/Grafana), and tune autoscaling and networking for high-throughput LLM workloads to ensure reliability and low latency.

Design, build, and deploy production-ready AI algorithms and high-scale evaluation pipelines focused on LLMs and patent generation. Implement advanced prompt engineering, translate research into product across the stack (Python, Postgres, React/TypeScript), and benchmark models to drive R&D decisions.

Design and build next-generation AI-assisted interfaces for complex IP workflows. Lead front-end architecture, rapidly prototype and ship features from user feedback, integrate advanced WYSIWYG editors, and contribute across the full stack to ensure robust, high-performance delivery as a founding engineering hire.

Lead development and production deployment of proprietary LLM-based algorithms and high-scale evaluation pipelines. Implement advanced prompt engineering, ship evaluation frameworks, and work across the stack (Python, Postgres, TypeScript/React) to translate research into production-ready AI products.

Build and scale core backend systems, contribute to a React-based frontend, translate customer feedback into product features, and help establish engineering culture and hiring.

Lead and design backend platform architecture, build data integrations and automations, guide a small multidisciplinary team, partner with Product, mentor engineers, unblock delivery, and ensure scalable, fault-tolerant systems for low-carbon tech deployments.

Lead design and ownership of backend platform components for Low Carbon Tech. Build scalable, fault-tolerant services, optimize databases, improve testing and non-functional requirements, mentor engineers, perform code reviews, and drive integrations and automations to scale EV chargers, solar, batteries and heat pumps into homes.

Lead design, build and evolve secure, reliable, scalable cloud platforms. Set technical direction, drive automation, support deployments, monitoring and incident response, coach engineers, and ensure regulatory and security alignment.

Design, build, and own end-to-end AI infrastructure and agentic workflows for private equity diligence: data ingestion, retrieval, orchestration, evals, and production reliability. Drive architecture decisions, measurement, and domain-specific systems to ensure enterprise-grade, low-hallucination outputs.

Early full‑stack engineer defining product DNA, building multi‑step LLM/agent workflows, owning end‑to‑end workspace and UI, translating consulting practices into software, and shipping prototypes rapidly while collaborating with technical and non‑technical stakeholders.

Hands-on data analyst role focused on operations analytics: build reporting baselines and dashboards, analyze workflows to find inefficiencies, use Python and SQL for deep-dive analysis, create proof-of-concept automations (APIs, LLMs), support QA/AML/fraud/customer support analyses, ensure data quality and metric consistency, and present insights to technical and non-technical stakeholders.

Own go-to-market and partner relationships for Zable non-credit products on price comparison sites. Launch integrations, track channel performance (volume, conversion, CAC), negotiate commissions, run commercial analysis, and collaborate with Product, Data, Pricing and Compliance to optimise acquisition and product strategy.