AI Platform Engineer

Apollo Solutions; Boston (MA); On-site; USD 140,000 - 200,000; Full time

Job summary

Apollo Solutions in Boston is hiring an AI Platform Engineer to design and build the underlying platform and infrastructure that enables AI across the business.

This role prioritizes platform engineering over building individual AI apps, focusing on shared services, APIs, and controls for scalable, secure AI deployments.

You will work across software engineering, cloud infrastructure, AI tech, and platform architecture, contributing to hands-on development and long-term technical direction.

Qualifications

• 5+ years of experience in software/platform engineering or related field.
• Experience building production software/platform solutions at scale.
• Strong understanding of distributed systems and service-based architectures.

Responsibilities

• Design and develop shared AI platform services used by engineering teams.
• Build scalable infrastructure enabling secure access to LLMs and foundation models.
• Develop backend services and APIs supporting AI workloads.
• Build platform capabilities around model integration, orchestration and runtime management.
• Design and maintain AI gateway services including routing, controls and governance.
• Develop MCP-related infrastructure: context management and tool integration.
• Create reusable platform components to simplify AI integration for apps.
• Collaborate with cloud and security teams to deploy and operate AI services.

Skills

Distributed systems

Cloud native

Kubernetes

IaC/CI-CD

Backend development

AWS/Azure

Security governance

Observability

Communication

Tools

Kubernetes

AWS

Azure

Terraform

CI/CD tooling

Linux

Job description

We are working with a large financial services organization that is continuing to invest in its AI and engineering capabilities.

They are looking for an AI Platform Engineer to help design and build the underlying platform and infrastructure that supports the use of AI across the business.

This is a platform focused engineering role rather than a position centered around building individual AI applications or chatbots. You will work on the shared services, APIs, infrastructure and controls that allow engineering teams to develop and deploy AI powered solutions securely and at scale.

The role will involve working across software engineering, cloud infrastructure, AI technologies and platform architecture, with the opportunity to contribute to both hands on development and longer term technical direction.

What You'll Be Doing

• Design and develop shared AI platform services used by engineering and technology teams across the organization.
• Build scalable infrastructure that enables secure access to large language models and foundation model technologies.
• Develop backend services and APIs supporting AI workloads and internal applications.
• Build platform capabilities around model integration, orchestration and runtime management.
• Design and maintain AI gateway services including model routing, usage controls and policy enforcement.
• Develop infrastructure supporting tool execution, context management and Model Context Protocol (MCP) services.
• Build reusable platform components that make it easier for engineering teams to integrate AI capabilities into their applications.
• Work with cloud and infrastructure teams to deploy and operate AI services across scalable environments.
• Partner with security teams to implement authentication, authorization, auditing and governance controls.
• Improve platform monitoring through logging, tracing, metrics and observability tooling.
• Contribute to the architecture and technical roadmap for the wider AI platform.
• Help establish engineering standards around testing, automation, deployment, reliability and maintainability.
• Troubleshoot complex platform issues and improve the performance and resilience of production services.

What We're Looking For

• 5+ years of professional experience in software engineering, platform engineering, infrastructure engineering or a related technical field.
• Strong experience building production software or platform solutions at scale.
• Experience designing and working with distributed systems and service based architectures.
• Hands on programming experience with Python, Java, Go or TypeScript.
• Experience developing backend services, APIs and reusable platform components.
• Strong understanding of cloud native technologies and containerized environments.
• Experience working with Kubernetes and modern cloud infrastructure.
• Knowledge of Infrastructure as Code, automation and CI/CD practices.
• Experience with public cloud environments such as AWS or Azure
• Understanding of generative AI infrastructure, LLM integrations or enterprise AI platforms.
• Familiarity with technologies and concepts such as RAG, model orchestration, AI gateways, tool calling or agent frameworks.
• Experience building secure platforms with appropriate identity, access and governance controls.
• Good understanding of monitoring, logging and observability within production environments.
• Strong communication skills with the ability to work across engineering, infrastructure, security and product teams.

Preferred Experience

• Experience with enterprise AI services such as Amazon Bedrock, Azure AI or similar technologies.
• Experience building internal platforms or shared services used by multiple engineering teams.
• Knowledge of Model Context Protocol (MCP) and AI tool integration.
• Experience with AI observability, model evaluation or governance tooling.
• Familiarity with model routing and environments that use multiple AI model providers.
• Experience working across cloud and hybrid infrastructure environments.
• Previous experience within financial services, investment management or another large enterprise environment.