Job description

Acadian Asset Management is a global, systematic investment manager at the forefront of data-driven investing since 1986. Headquartered in Boston, with locations in Singapore, London, and Sydney, we manage over $232 billion on behalf of leading institutions worldwide—including pension funds, endowments, foundations, and sovereign wealth funds. We harness advanced technology, rich datasets, and multidisciplinary expertise to help clients navigate complex markets and uncover insights that may be overlooked by traditional approaches. What sets Acadian apart is our people. We foster a collaborative, intellectually curious environment where ideas are tested, diverse perspectives are welcomed, and innovation thrives. We’re united by a shared purpose: delivering effective client outcomes and supporting one another in work that’s both challenging and rewarding. We offer a flexible hybrid work environment, strong benefits, and a casual but focused office culture—all designed to support the meaningful, collaborative work that defines Acadian. Position Overview: The Platform team is responsible for building and supporting services that enable our development teams to leverage frameworks, tooling, and services across in-house and vendor PaaS/IaaS offerings. Platform defines the architectural roadmap, best practices, and provides education on these services. This position will work on a cross-functional team that is responsible for implementation and maintenance of our investment infrastructure, focusing on building reusable application templates, patterns of delivery, and operational support of our systems running in AWS and Kubernetes. You will partner with development teams in the Investment group and peers in Platform to improve how we operate our applications. Platform's goal is to enable our fellow product focused teams to deliver solutions faster through automation and engineering. Acadian supports a hybrid work environment; employees are on-site in the Boston office 3 days a week. What You’ll Do: Pair with your team members to build out services and tools that advance our cloud capabilities using AWS services like EKS, ECS, EC2, Lambda, Bedrock, and Parallel Computing Service (PCS) Build and extend reusable infrastructure-as-code components — Terraform, CDK8s, Crossplane, etc — so product teams get secure, well-instrumented defaults out of the box Operate and improve our GitOps delivery model on Kubernetes using ArgoCD, Helm, and Kustomize, and extend the cluster platform with Crossplane and EKS add-ons Use AI-assisted development tooling in your daily work and help build the automation and guardrails that make it safe and repeatable for other teams Support the infrastructure behind our AI and quantitative research workloads, including Bedrock-hosted models and HPC compute Drive automation of the entire software delivery lifecycle in GitLab CI, including testing and policy checks for infrastructure code Ensure observability and availability of the investment systems using OpenTelemetry, New Relic, and CloudWatch, and help define meaningful service-level objectives Build security in by default — secrets managed through Vault and Secrets Manager, least-privilege IAM, and container and dependency scanning in the pipeline Help keep cloud spend efficient through right-sizing, autoscaling, and cost visibility Review, comment, and approve pull/merge requests Proactively improve and modernize our tech stack Troubleshoot and resolve operational issues Contribute to runbooks, documentation, and team knowledge sharing Rotate through an on-call schedule with your team members to provide after-hours support when needed We're Looking for Teammates With: BS in Computer Science or related field preferred with at least 3 years of prior engineering experience (Financial services exposure is a plus) Experience building and operating scalable, durable services in AWS Demonstrated working experience with Linux, containers, and Kubernetes Experience with Terraform, Helm, and Kustomize (CDK/CDKTF experience is a plus) Experience developing services/libraries in Python and at least one of TypeScript, Go, or C# (all are relevant to our current stack) Familiarity with CI/CD and GitOps tooling such as GitLab CI, and ArgoCD Knowledge of observability platforms such as OpenTelemetry, CloudWatch, New Relic, Prometheus Practical use of AI coding assistants in day-to-day engineering work, and a working understanding of modern AI concepts — LLM APIs, retrieval, agentic workflows, and tool/context protocols such as MCP Familiarity with secrets management and cloud security fundamentals (Vault, IAM, least privilege) Familiarity with scripting in Bash/POSIX Shell Knowledge of common patterns and software architecture Exposure to migration strategies for legacy workloads to AWS Structured approach to troubleshooting Practical experience with networking and storage The base salary range for this role is $155,000 – $175,000 per year. Actual compensation will be determined based on a candidate’s skills, qualifications, and relevant experience. In addition to base pay, this position may be eligible for discretionary incentive compensation and includes participation in Acadian’s comprehensive benefits program, which includes health, retirement, and wellness offerings. To apply for this position or view Acadian’s open roles, please visit the Careers section of our website at: [application link] . We will contact only selected candidates. If you are a candidate with a disability, or are assisting a candidate with a disability, and require an accommodation to apply for one of our jobs, please email us at recruiting@acadian-asset.com. Acadian Asset Management LLC is committed to providing equal employment opportunity to all employees and applicants. No employee or applicant shall be discriminated against on the basis of gender, race, creed, color, sex, age, national origin, marital status, pregnancy or parenthood, veteran status, citizenship status, disability, gender identity, or sexual orientation.

Requirements

Must-haves

Acadian supports a hybrid work environment; employees are on-site in the Boston office 3 days a week.
Pair with your team members to build out services and tools that advance our cloud capabilities using AWS services like EKS, ECS, EC2, Lambda, Bedrock, and Parallel Computing Service (PCS)
Build and extend reusable infrastructure-as-code components — Terraform, CDK8s, Crossplane, etc — so product teams get secure, well-instrumented defaults out of the box
Operate and improve our GitOps delivery model on Kubernetes using ArgoCD, Helm, and Kustomize, and extend the cluster platform with Crossplane and EKS add-ons
Use AI-assisted development tooling in your daily work and help build the automation and guardrails that make it safe and repeatable for other teams
Support the infrastructure behind our AI and quantitative research workloads, including Bedrock-hosted models and HPC compute
Drive automation of the entire software delivery lifecycle in GitLab CI, including testing and policy checks for infrastructure code
Ensure observability and availability of the investment systems using OpenTelemetry, New Relic, and CloudWatch, and help define meaningful service-level objectives
Build security in by default — secrets managed through Vault and Secrets Manager, least-privilege IAM, and container and dependency scanning in the pipeline
Help keep cloud spend efficient through right-sizing, autoscaling, and cost visibility
Review, comment, and approve pull/merge requests
Proactively improve and modernize our tech stack
Troubleshoot and resolve operational issues
Contribute to runbooks, documentation, and team knowledge sharing
Rotate through an on-call schedule with your team members to provide after-hours support when needed
Experience building and operating scalable, durable services in AWS
Demonstrated working experience with Linux, containers, and Kubernetes
Experience developing services/libraries in Python and at least one of TypeScript, Go, or C# (all are relevant to our current stack)
Familiarity with CI/CD and GitOps tooling such as GitLab CI, and ArgoCD
Knowledge of observability platforms such as OpenTelemetry, CloudWatch, New Relic, Prometheus
Practical use of AI coding assistants in day-to-day engineering work, and a working understanding of modern AI concepts — LLM APIs, retrieval, agentic workflows, and tool/context protocols such as MCP
Familiarity with secrets management and cloud security fundamentals (Vault, IAM, least privilege)

Nice-to-haves

BS in Computer Science or related field preferred with at least 3 years of prior engineering experience (Financial services exposure is a plus)
Experience with Terraform, Helm, and Kustomize (CDK/CDKTF experience is a plus)

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

awskubernetesaipythontypescriptgoci/cdllm

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Wellness