Staff Software Engineer- AI Platform
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Before you apply
Salary$176k – $238k
LocationRemote, United States
Work moderemote
Typefull-time
SeniorityLead
Experience8+ yrs
DepartmentTechnology, Engineering
EquityIncluded
Company size38+ people
PostedOct 22, 2026 · 2w ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
BS/BTech (or higher) in Computer Science, Engineering or a related field required
8+ years of production-level experience as an engineer building highly scalable systems
4+ years of experience acting as a trusted technical decision-maker in a team setting
4+ years of experience working with SQL or other database querying languages on large multi-table data sets
Experience architecting, developing, and deploying large-scale distributed systems at scale
Experience with cloud technologies, e.g., AWS, Azure, GCP
Experience building continuous integration and continuous development (CI/CD) pipelines
Strong familiarity with server-side web technologies (eg: Java, Python, Scala, C#, C++, Go)
Experience building or operating production platform infrastructure, distributed systems, developer platforms, or other high-availability shared services
Experience with LLM infrastructure, model gateways, foundation model APIs, or managed AI platforms such as AWS Bedrock, Azure OpenAI, Google Vertex AI, or similar technologies
Strong experience with cloud infrastructure, preferably AWS, and technologies such as Kubernetes, containers, and infrastructure as a code
Experience designing observability and operational practices for production systems
Experience designing APIs and self-service platform capabilities used by other engineering teams
Experience with Identity, access control, secrets management, security and governance for shared infrastructure
Experience with cost management, usage attribution, quotas, budgets, or capacity management for shared platforms
Experience operating systems that handle sensitive or regulated data
Ability to evaluate architectural tradeoffs across reliability, performance, security, cost, scalability and developer experience
Skills
SQL
AWS
Azure
GCP
Java
Python
Scala
C#
C++
Go
Kubernetes
AWS Bedrock
Azure OpenAI
Google Vertex AI
Benefits
Performance bonus
Equity
About the role
As a Staff Software Engineer on Aledade’s AI Core Platform team, you will help build and operate the shared infrastructure that enables applications and AI agents across Aledade to securely and reliably access foundation models.
You will work on the platform capabilities behind model access, including model gateways, cloud AI services, provider integrations, routing and fallback, usage controls, observability, reliability, and model governance.
We’re looking for engineers who think beyond implementing individual features and consider the full lifecycle of production platform systems: architecture, scalability, failure modes, security, observability, operational readiness, cost, and developer experience. You will help evolve the platform as AI adoption grows across Aledade, building reusable and self-service capabilities rather than one-off solutions.
You will work closely with engineers, product partners, security, infrastructure teams, and teams building AI applications and agents. Successful engineers in this role are comfortable operating in ambiguous problem spaces, making pragmatic technical decisions, and building secure, maintainable, observable, and resilient systems.
Primary Duties:
•
Identify and develop scalable and performant solutions.
•
Work across discipline to shape product strategy and execution.
•
Develop the foundations of code architecture and quality.
•
Mentor and coach engineers.
•
Set and uphold the standard for engineering processes to support high-quality engineering.
Minimum Qualifications:
•
BS/BTech (or higher) in Computer Science, Engineering or a related field required.
•
8+ years of production-level experience as an engineer building highly scalable systems.
•
4+ years of experience acting as a trusted technical decision-maker in a team setting, solving for short-term and long-term business value.
•
4+ years of experience working with SQL or other database querying languages on large multi-table data sets.
•
Experience architecting, developing, and deploying large-scale distributed systems at scale.
•
Experience with cloud technologies, e.g., AWS, Azure, GCP.
•
Experience building continuous integration and continuous development (CI/CD) pipelines.
•
Strong familiarity with server-side web technologies (eg: Java, Python, Scala, C#, C++, Go).
Preferred KSAs:
AI Infrastructure & Model Platform:
•
Experience building or operating production platform infrastructure, distributed systems, developer platforms, or other high-availability shared services.
•
Experience with LLM infrastructure, model gateways, foundation model APIs, or managed AI platforms such as AWS Bedrock, Azure OpenAI, Google Vertex AI, or similar technologies.
•
Strong experience with cloud infrastructure, preferably AWS, and technologies such as Kubernetes, containers, and infrastructure as a code.
•
Experience designing observability and operational practices for production systems, including metrics, distributed tracing, logging, alerting, SLOs, dashboards and failure handling.
•
Experience designing APIs and self-service platform capabilities used by other engineering teams.
•
Experience with Identity, access control, secrets management, security and governance for shared infrastructure.
•
Experience with cost management, usage attribution, quotas, budgets, or capacity management for shared platforms.
•
Experience operating systems that handle sensitive or regulated data.
•
Ability to evaluate architectural tradeoffs across reliability, performance, security, cost, scalability and developer experience.
Physical Requirements:
Sitting for prolonged periods of time. Extensive use of computers and keyboard. Occasional walking and lifting may be required.
Benefits
Base salary range: $176,000 – $238,000 USD annually
The range above reflects the base pay we reasonably expect to offer for this role across all U.S. locations. Where an individual offer lands within the range depends on the candidate’s skills, relevant experience, qualifications, scope of the role, and internal equity. This role is eligible for an annual performance bonus/incentive and equity compensation in addition to the benefits listed below.