Elliptic

Do you thrive in a fast-paced setting where you can shape DevOps culture, drive automation, and deliver real impact across engineering teams? Elliptic is seeking a Lead DevOps Engineer to define and execute our next-generation platform vision. You will guide a growing team of DevOps engineers to deliver automation, scalability, security, and operational excellence across our multi-site Kubernetes infrastructure. We're looking for a hands on leader, someone who can balance deep technical expertise with people leadership, operational strategy, and continuous improvement. You will partner closely with Engineering, Security, and Data teams to create a culture of reliability, shared ownership, and constant innovation. The impact you will have: Set the technical and cultural direction for DevOps at Elliptic, aligning our infrastructure strategy with company goals. Scale our engineering platforms globally, evolve our reliability posture, and mentor a skilled team that's trusted to run high availability production systems supporting mission critical workloads. Bridge the gap between executive direction and technical delivery, ensuring our systems are both high performing today and ready for what's next. What you will do: Own, build, and evolve the DevOps and Platform Engineering roadmap, defining the technical backbone for automation, scaling, and multi tenant Kubernetes based IDP. Lead, by doing, engineering, reviewing, and improving Kubernetes and CNCF aligned infrastructure daily, setting the technical benchmark for excellence. Architect and operate multi cluster, multi region Kubernetes environments using tooling such as Istio/Linkerd (service mesh federation), Cluster API (lifecycle management), and Kyverno (policy as code). Design and deploy progressive delivery frameworks with Flux and Flagger for GitOps driven releases, canary and A/B deployments, and automated rollout health checks. Implement modern infrastructure provisioning via controllers such as Crossplane and ACK for Kubernetes native integration between cloud infrastructure and application delivery. Define and enforce Zero Trust architecture, implementing network and identity hardening through HashiCorp Vault (secrets management), Boundary (access broker), service identity, and secure service mesh mTLS. Engineer policy driven automation and compliance frameworks, leveraging OPA, Kyverno, and secure supply chain and runtime configurations. Develop and maintain IaC and GitOps standards and introduce automated testing for every infrastructure change. Prototype and integrate agentic infrastructure components, including Agentic deployment and observability platforms within Kubernetes service meshes. Design and integrate AI Gateways and Registries that route traffic and events between microservices and autonomous agents through CNCF Gateway API constructs. Champion DevSecOps maturity and experimentation, embedding SAST/DAST, chaos engineering, and error budget tracking to drive continuous improvement. Collaborate cross functionally with Security, Data, and AI engineering to shape the intersection of DevOps and agentic AI platform architectures for high integrity, regulatory compliant operations. Continuously research and adopt emerging CNCF and AI ecosystem advancements, from eBPF observability to agent aware orchestration, to keep Elliptic at the forefront of DevOps innovation. You will be a great fit here if you: Have a passion for building reliable, secure, and scalable systems, and leading others to do the same. Thrive on setting strategy and rolling up your sleeves to implement it. Are driven by a strong customer and product focus. Embrace ownership and decision making in fast moving environments. Want to build high performing, autonomous teams and shape DevOps culture at scale. Align technical leadership with business outcomes. Are transparent, collaborative, and committed to learning and improvement. Our ideal candidate has production experience with most of the following: Platform as Product expertise, defining vision, roadmaps, and user research loops for internal developer platforms (IDPs). Deep Kubernetes expertise including full cluster lifecycle management, API extension, custom Operator development, Helm charts, and working across the CNCF ecosystem (addons such as Cilium, ExternalDNS, Kyverno, Gatekeeper). Designing and operating multi cluster, multi region Kubernetes deployments with service meshes (Istio, Consul, Linkerd) and policy based workload placement. Advanced networking - service mesh federation, mTLS at scale, and eBPF/Cilium observability tracing. Writing Infrastructure as Code using Terraform against AWS / GCP, with modular architectures, state segmentation, GitOps integration, automated testing (Terratest/InSpec), and controlled version promotion. Provisioning and governing cloud resources using Kubernetes native controllers such as Crossplane, ACK, or KRO, aligning infrastructure and application delivery. Implementing GitOps pipelines with ArgoCD or FluxCD, enabling progressive delivery, automated drift correction, and multi environment deployments. Building cloud native container, serverless, and event driven systems grounded in observability and resilience, with tracing, metrics, and logs correlated through DataDog, Splunk, or OpenTelemetry. Managing platform security through Vault based secret management, least privilege access with HashiCorp Boundary or AWS IAM policies, and compliance automation. Establishing robust CI/CD architectures integrating SAST/DAST, policy enforcement, and cost/performance telemetry. Applying SLOs, error budgets, and chaos engineering to continuously improve reliability and service quality. Leading DevOps culture initiatives, building self service developer platforms, defining golden paths, and coaching teams in platform driven delivery. Bonus Points for experience with: Leadership of platform modernisation or reliability programs in scale up or regulated environments. Production experience with Kubernetes Operator development and CRD lifecycle automation. Implementation or design experience with eBPF, service mesh federation, and Cilium based tracing for network and security observability. Policy as code and governance automation using OPA / Kyverno, tied into Secure Supply Chain or CSPM frameworks. Hands on exposure to AI driven internal developer platforms, integrating telemetry and observability powered by AI or LLMs for predictive insights and adaptive remediation. Experience architecting agentic infrastructures, including observability pipelines and experimentation frameworks for AI agents. Familiarity with MCP and A2A orchestration patterns running on Kubernetes, enabling agents to communicate through secure service meshes. Working knowledge of Agent Gateways and Registries, bridging microservices and AI agents through Gateway API and service mesh constructs. Experience experimenting with secure containers, sandboxing, and confidential computing for blockchain or regulated workloads. Experience with data oriented workloads, spark, Databricks, or Data Mesh. Programming proficiency in Go, Python, or TypeScript. Open source contributions or community leadership in CNCF related projects. Job Benefits How we work Hybrid working and the option to work from almost anywhere for up to 90 days per year. £500 Remote working budget to set up your home office space. Learning & Development $1,000 Learning & Development budget to use on anything that contributes to your growth and development. Vacation / Leave Holidays: 25 days of annual leave plus bank holidays. An extra day for your birthday. Enhanced parental leave: we provide eligible employees, regardless of gender or whether they become a parent by birth or adoption, 16 weeks fully-paid leave. Benefits Private Health Insurance - we use Vitality. Full access to Spill Mental Health Support. Life Assurance: cover for 4 times your salary to your beneficiaries. £100 crypto for you. Cycle to Work Scheme. We know Diversity and Inclusion is much deeper than just hiring, but it's important for us to mention it here. We welcome and embrace individuals of all backgrounds and identities at Elliptic, and this is an ongoing priority for us. We believe our diverse team of individuals underpins this by bringing creative thinking and innovation to Elliptic every day. We are committed to creating a diverse, inclusive and equitable workplace, so we welcome applications from everyone, even if you may not think you fit all of the requirements of our roles. We foster an environment of psychological safety, where everyone feels comfortable to bring their whole self to work.

Elliptic is looking for a Lead DevOps Engineer to spearhead our platform vision, focusing on automation, scalability, and team leadership. This pivotal role involves defining the DevOps roadmap, managing multi-site Kubernetes infrastructure, and collaborating with Engineering and Security teams. The ideal candidate thrives in fast-paced environments, has deep technical knowledge, and is passionate about fostering a high-performing DevOps culture. Benefits include hybrid working options, generous learning budgets, and enhanced parental leave.

The impact you will have As Staff MLOps Engineer, you will define and build Elliptic's Enterprise MLOps platform. Elliptic has growing ML capability across several teams, an established model registry, and a maturing model risk management practice. What is missing is the unified platform layer that ties training, deployment, monitoring, and governance together into a coherent, scalable discipline. You will be responsible for creating that layer. Your platform will serve four distinct internal consumers, each with different needs: Product Engineering teams building customer-facing models and customer data analytical models, who need reproducible training pipelines, CI/CD for model deployment, and low-latency serving infrastructure Intelligence Research building frontier intelligence collection, predictive pre-screening models, and behavioural pattern detection, who need rapid experimentation, GPU orchestration, and dataset versioning InfoSec who own the model registry and model risk management framework today, and need the platform to close execution gaps in audit trails, drift monitoring, and compliance reporting Operations who own BI, usage prediction, and revenue opportunity signalling, and need scheduled batch inference, BI integration, and pipeline reliability The platform you build must enforce governance with enough rigour to satisfy a regulated financial crime context, while remaining flexible enough to avoid slowing down research teams who need to iterate quickly. This is a role for someone who has built ML infrastructure from the ground up before, who understands that a platform succeeds only when it is adopted, and who is comfortable making build vs buy decisions that others will adopt and use for years. What you will do Define the target state MLOps architecture for Elliptic, covering model training pipelines, serving infrastructure, monitoring, feature management, and governance, and produce the architecture decision records that inform investment decisions Make and document build vs buy vs stop recommendations with clear cost modelling and trade off analysis, evaluating vendors, open-source tools, and managed services against Elliptic's constraints (AWS primary, Databricks ecosystem) Work with InfoSec to improve the existing model registry and model risk management framework, closing identified gaps in metadata, lineage, approval workflows, and drift/bias detection Build model training pipelines, CI/CD for ML, and serving infrastructure, working directly with a small group of infrastructure engineers to ship production grade platform capabilities Instrument observability across the ML lifecycle: training metrics, serving latency and throughput, data quality, and prediction drift, integrating with Elliptic's existing observability stack Work directly with data scientists and ML engineers across all four consumer groups to onboard them onto the platform, writing documentation, runbooks, and reference architectures that lower the barrier to self service You will be a great fit here if you Have built MLOps platforms or ML infrastructure from the ground up, and can speak to what worked, what didn't, and why Have operated in a regulated industry (e.g. compliance, financial) and have hands on experience building ML infrastructure to meet those regulatory demands Think about ML infrastructure the way the best platform engineers think about data infrastructure: as a set of foundations with internal customers whose needs must be understood and balanced Are comfortable operating in ambiguity, making decisions with incomplete information, and creating structure where none exists, while remaining open to changing course when better information arrives Influence through clarity, evidence, and the quality of your work rather than positional authority. You earn adoption by making the platform genuinely better than the alternative Care about production engineering quality: you write production grade code, your systems are tested, observable, documented, and designed for others to operate Our ideal candidate has Deep hands on experience building MLOps platforms, including model registries, feature stores, and ML pipeline orchestration Working knowledge of model serving patterns: real time inference, batch prediction, A/B deployment, and deployment strategies AWS infrastructure experience (ECS/EKS, S3, IAM, networking) and comfort operating in a Databricks ecosystem or equivalent lakehouse architecture Experience with model monitoring: model evaluation, data drift detection, prediction drift, and performance degradation alerting A track record of building something from zero and bringing it to a state where others could operate and extend it Experience in a regulated industry (fintech, financial services, healthcare) where model governance is a compliance requirement See AI as a core part of how modern engineering gets done, not a passing trend. You actively use it to think faster, prototype faster, and pressure test your own designs, and you're excited that the bar keeps rising. Prior experience running formal build vs buy evaluations with written decision records Bonus Points for Familiarity with model risk management frameworks and the ability to connect governance practices to regulatory expectations Experience working simultaneously with research oriented ML teams and production oriented engineering teams, and understanding how their needs diverge Infrastructure as code fluency (Terraform) Experience with ClickHouse or similar OLAP engines for low latency ML feature serving Blockchain or crypto domain knowledge Experience working in fraud detection and modelling Contributions to open source MLOps tooling Job Benefits How we work Hybrid working and the option to work from almost anywhere for up to 90 days per year £500 Remote working budget to set up your home office space Learning & Development $1,000 Learning & Development budget to use on anything (agreed with your manager) that contributes to your growth and development Vacation/ Leave Holidays: 25 days of annual leave + bank holidays An extra day for your birthday Enhanced parental leave: we provide eligible employees, regardless of gender or whether they become a parent by birth or adoption, 16 weeks fully paid leave and leave. Benefits Private Health Insurance - we use Vitality! Full access to Spill Mental Health Support Life Assurance: we hope you will never need this - but our cover is for 4 times your salary to your beneficiaries £100 Crypto for you! Cycle to Work Scheme

Elliptic is hiring an engineer for their Collection Engineering team in London. The role involves building tools that enhance intelligence operations for law enforcement and financial institutions to combat crypto crime. Ideal candidates will have strong Typescript skills, a passion for cryptocurrencies, and at least 3 years of commercial experience. The position offers benefits like private health insurance, a learning budget, and 25 days of annual leave along with a hybrid working model.

A leading blockchain intelligence firm is seeking a Senior Software Engineer to design and implement large-scale distributed data systems. You will drive technical direction and collaborate across teams to deliver impactful solutions in the crypto space. The ideal candidate has a strong background in data engineering, experience with tools such as Scala, Spark, and AWS, and is excited to mentor junior engineers. This role offers hybrid working options and substantial learning and development budgets.

Elliptic is seeking a Staff AI Engineer to play a pivotal role in the company's AI expansion. In this impactful position, you'll govern architectural decisions and evaluate tooling for AI products. Ideal candidates will have experience in AI architectural decisions, with an understanding of both internal tooling and customer-facing products. You will work collaboratively across teams and develop clear foundational documents for AI systems. This role offers hybrid working options and a competitive benefits package, including a £1,000 learning budget and private health insurance.

The impact you will have: As Staff AI Engineer, you will be one of the most impactful early hires in Elliptic's next stage of AI expansion. You will join at a moment when Elliptic is actively forming its approach to AI foundations: tooling decisions are being made, agentic patterns are being established, and the kernel of a centralised AI platform is being laid out. Your role is to govern the quality and coherence of those decisions before they crystallise. You will initially work across our AgentForce and Investigations & AI teams, holding the architectural bar on tooling evaluations, keeping the stack decision open and well-reasoned, and ensuring that the internal agentic patterns being developed today are genuinely inheritable by the customer-facing AI products of tomorrow. You will act as a strong advocate for AI adoption, AI technical best practices, and AI enablement across product, engineering, and development. This is a role for someone who is comfortable with ambiguity, energised by the challenge of making decisions that others will build on for years, and confident enough to hold a strong technical position without needing a team beneath them to do it. What you will do: Serve as the architectural conscience for Elliptic's early AI decisions, evaluating our current tooling explorations (including the LangSmith ecosystem and Databricks) against the requirements of production-scale, customer-facing AI products, and producing a clear, evidence-based recommendation Work consultatively with the Investigations & AI technical lead and AgentForce engineering to ensure that internal agentic patterns, prompt architectures, and evaluation frameworks are being designed with customer-facing scale and regulatory auditability in mind Hold the AI stack decision open responsibly: document trade-offs, establish evaluation criteria, and prevent pragmatic local choices from defaulting the answer before the right person is in place to make it Define and uphold engineering standards for AI systems across the organisation: model observability and tracing, prompt versioning and registry, cost governance, evaluation harnesses, and agent reliability patterns Produce the technical foundation documents that will be a coherent architectural position, a clear view of decisions made and decisions deferred, and an honest assessment of what the architecture can accomplish You will be a great fit here if you: Are energised by the challenge of bringing rigour to early-stage technical decisions, and understand that preventing a bad architectural choice is often more valuable than shipping a feature Can hold a strong, well-reasoned technical position without needing formal authority to make it stick. You influence through clarity, evidence, and the quality of your thinking Think about AI infrastructure the way the best platform engineers think about data infrastructure: as a set of foundations with internal customers whose needs must be understood and balanced Are comfortable operating in ambiguity and working across teams without a fixed mandate, and know how to make yourself useful in a way that doesn't create dependency or territorial friction Care about the trustworthiness of AI systems, not just their capability. Understand why explainability, auditability, and reliability matter especially in a regulated compliance context Our ideal candidate has: Made production AI architectural decisions, including evaluation framework selection, LLM integration patterns, prompt management and versioning at scale, and model observability. You can speak to what went well, what they would do differently, and why Worked across the boundary between internal tooling and customer-facing AI products, and understands how requirements differ across those contexts, particularly in relation to reliability, auditability, and cost Built or significantly shaped an AI evaluation or observability framework in a production environment, and has strong opinions on what good looks like Operated effectively without a team beneath them. As a Staff IC whose impact comes from technical leadership and cross-team influence rather than people management and team workstream prioritisation Bonus Points for: Experience building agentic systems in a production context, including orchestration patterns, tool use, memory management, and agent reliability at scale Familiarity with one of the major AI ecosystems, such as LangSmith, MLflow, or Databricks ML Having navigated a transition from a scrappy, point-to-point AI integration to a well-engineered, reusable AI platform. An understanding of the organisational as well as technical challenges that transition involves An interest in the crypto ecosystem and the mission of making digital assets safer and more accessible Job Benefits Hybrid working and the option to work from almost anywhere for up to 90 days per year £500 Remote working budget to set up your home office space $1,000 Learning & Development budget to use on anything (agreed with your manager) that contributes to your growth and development Holidays: 25 days of annual leave + bank holidays An extra day for your birthday Enhanced parental leave: we provide eligible employees, regardless of gender or whether they become a parent by birth or adoption, 16 weeks fully-paid leave and leave. Private Health Insurance - we use Vitality! Full access to Spill Mental Health Support Life Assurance: we hope you will never need this - but our cover is for 4 times your salary to your beneficiaries £100 Crypto for you! Cycle to Work Scheme

Do you want to help define the future of blockchain intelligence? Are you passionate about data, distributed systems, and delivering impact at scale? Are you looking for a values driven company that invests in its people and gives you the autonomy to shape critical systems? We're looking for a Senior Software Engineer to join Elliptic's Product Engineering organisation, focusing on data engineering solutions that power our analytics and intelligence products. As a senior member of the team, you will drive the technical direction of our data platform, ensuring it continues to meet the growing demands of blockchain analysis. Challenges include building a blockchain agnostic solution that scales globally, processing large batch and streaming datasets, and solving complex data processing problems that give our customers deep insights into the flow of value across the crypto ecosystem. The impact you will have: Our data and intelligence platform sits at the heart of everything we do. As a senior engineer, you will design and implement data systems that serve as the backbone of all Elliptic products. You will collaborate across blockchain, intelligence and product teams to deliver innovative features and scalable architectures that help the world fight financial crime and increase transparency in the crypto space. You will also mentor engineers, champion best practices, and influence cross team decisions that shape how Elliptic processes and delivers blockchain intelligence data. What you will do: Architect, design, and implement large scale distributed data systems and pipelines. Contribute to technical decision making across batch and streaming data solutions. Collaborate with engineers, product managers, data scientists, and intelligence analysts to build customer focused products. Explore and integrate new technologies (e.g. data orchestration or cloud native tools) to optimise performance and scalability. Take shared ownership of data systems, from design to deployment and ongoing improvement and support. Perform thoughtful peer reviews that raise code quality and share best practices across the team. Contribute to platform wide initiatives that improve reliability, observability, and cost efficiency. Help shape the technical roadmap for data engineering across Elliptic. Tech environment: Scala Spark Databricks AWS GCP Airflow Kubernetes Terraform Functional Programming We value depth in any modern data ecosystem. If you're strong in equivalent technologies and excited to learn Scala, we'll support you in the transition. You will thrive here if you: Enjoy end to end ownership, from architecture design to coaching others through delivery. Strive for engineering excellence and scalable, sustainable systems. Use data and experimentation to guide decisions. Communicate openly and collaborate across teams. Support and coach less experienced engineers. Believe every challenge is an opportunity to simplify and innovate together. What we are looking for: Ability to design, build, and maintain distributed data systems in a cloud based environment. Hands on experience with big data frameworks such as Spark or Databricks (or a willingness to learn). Knowledge of cloud infrastructure (AWS, GCP, or Azure). Judgement to balance scalability, performance, and maintainability. Experience or interest in functional programming, data modelling, workflow orchestration, or AI driven tools. If you don't meet every criterion but are excited about this role, we encourage you to apply. Bonus Points for: Experience in stream processing frameworks and event driven architecture. Hands on experience with Infrastructure as Code (Terraform, CloudFormation). Experience working in containerised environments (Docker, Kubernetes). Interest in crypto and blockchain technologies. Job Benefits Hybrid working and the option to work from almost anywhere for up to 90 days per year. £500 Remote working budget to set up your home office space. $1,000 Learning & Development budget to use on anything (agreed with your manager) that contributes to your growth and development. Holidays: 25 days of annual leave + bank holidays. An extra day for your birthday. Enhanced parental leave: we provide eligible employees, regardless of gender or whether they become a parent by birth or adoption, 16 weeks fully paid leave and leave. Private Health Insurance - we use Vitality! Full access to Spill Mental Health Support. Life Assurance: we hope you will never need this - but our cover is for 4 times your salary to your beneficiaries. £100 Crypto for you! Cycle to Work Scheme. We know Diversity and Inclusion is much deeper than just hiring, but it's important for us to mention it here. We welcome and embrace individuals of all backgrounds and identities at Elliptic, and this is an ongoing priority for us. We know incredible people don't all think in the same way. We want to be challenged every day. We believe our diverse team of individuals underpins this by bringing creative thinking and innovation to Elliptic every day. We are committed to creating a diverse, inclusive and equitable workplace, so we welcome applications from everyone, even if you may not think you fit all of the requirements of our roles. We foster an environment of psychological safety, where everyone feels comfortable to bring their whole self to work.

Elliptic is looking for a Senior AI Engineer to enhance its AI products that assist compliance teams in tackling financial crimes. You will design agentic workflows and bring LLM-based features to production, working closely with a talented team. Your role will include leading technical decisions, mentoring junior engineers, and ensuring robust integration of AI capabilities across Elliptic's platform. The ideal candidate will have significant software engineering experience, particularly in LLM frameworks, and strong backend development skills.