2 days ago
Raleigh, NC, USA or Dallas, TX, USASenior
Responsibilities
- Design, build, and operate secure, scalable AI and agent platforms on AWS and comparable enterprise clouds.
- Own platform architecture across infrastructure, AI services, identity, networking, observability, and runtime operations.
- Automate infrastructure and delivery using Terraform, AWS CDK, and related tooling.
- Deploy and support production LLM and agent workloads using Amazon Bedrock and AWS services.
- Build resilient distributed systems with asynchronous processing, durable state, retries, idempotency, and recovery.
- Own agent-runtime reliability, including scaling, performance, observability, service-level objectives, incident response, recovery, and cost optimization.
- Implement identity, authorization, encryption, secrets-management, and auditable data and tool-access controls.
- Govern model access, quotas, provider onboarding, evaluation, and lifecycle controls.
- Partner with engineering, architecture, security, product, and business teams to establish reusable standards and patterns.
Requirements
- At least 5 years of software engineering experience, including at least 1 year delivering LLM or agent-based applications in production.
- Experience in cloud, platform, site reliability, or software engineering with responsibility for production systems.
- Strong enterprise-cloud experience across identity, networking, compute, storage, and event-driven architectures.
- Hands-on AWS experience or deep experience with another enterprise cloud transferable to AWS.
- Experience with infrastructure as code, containerized workloads, and automated delivery using Terraform, AWS CDK, Docker, ECS, EKS, or comparable cloud-native technologies.
- Experience building or operating production LLM, generative AI, or agent applications using model APIs, structured outputs, tool integration, retrieval, or comparable patterns.
- Experience designing or operating distributed systems with asynchronous processing, state management, retries, idempotency, resilience, and recovery.
- Working knowledge of observability, incident response, cost management, and enterprise security practices.
- Strong analytical, troubleshooting, communication, and collaboration skills.
- Preferred qualifications include 7 or more years of cloud, platform, or software engineering experience, substantial production AWS and architecture experience, shared-platform or internal-developer-product experience, architecture leadership or mentoring, agentic AI platforms, identity standards, AI governance, and regulated-environment experience.
- Relevant cloud, security, platform, or AI certifications, or equivalent practical experience, are preferred.
Benefits
- Remote and hybrid working arrangements are available.
- Fully paid comprehensive health and well-being benefits are provided.
- HedgeServ offers career development frameworks, structured learning paths, training, progression plans, and leadership development.
Categories
About HedgeServ
HedgeServ provides fund administration and middle- and back-office services for alternative asset managers, delivered through a proprietary platform plus staffed operations. Offerings span fund accounting, investor services, risk and compliance, data aggregation, and portfolio reporting across hedge funds, private equity, private credit, real estate, and other vehicles. Founded in 2008 and headquartered in Dallas, it is privately held with more than $700 billion in assets under administration and offices across North America, Europe, and Asia-Pacific.