AI Platform Engineer
Responsibilities
Qualifications & Requirements
Experience Level: Senior Level
Full Job Description
Ahead is seeking an experienced AI Platform Engineer to join our team in Hyderabad. In this hands-on role, you will be instrumental in building and maintaining the technical infrastructure for our Enterprise Insights Platform. This platform leverages Glean as its core Work AI and GPT layer, serving as a central hub for low-code/no-code AI tools. You will collaborate closely with Product Owners, AI Platform Administrators, Enterprise AI, security, and application teams to deliver innovative AI solutions.
Core Responsibilities
- Platform & Integrations: Design and develop robust backend services and integrations to expose Glean/LLM capabilities to internal applications and seamlessly connect with critical enterprise systems, including SaaS, data platforms, and line-of-business applications.
- AI App Store & Agents: Implement the backend infrastructure for an internal AI app store or marketplace for Glean agents and workflows. This includes managing the catalog, metadata, approval processes, and permissions.
- Agent Lifecycle & CI/CD: Establish agent promotion and release processes across development, testing, and production environments. Build and maintain CI/CD pipelines (e.g., AWS CodePipeline, GitHub Actions, GitLab CI) for agents, workflows, and supporting services.
- Cloud Infrastructure & IaC: Design, deploy, and manage AWS infrastructure using Infrastructure as Code principles with Terraform or AWS CDK. Containerize workloads using Docker and deploy them on ECS Fargate or EKS.
- Observability & Reliability: Configure CloudWatch and OpenTelemetry for comprehensive LLM observability, including latency, error rates, and token usage. Implement robust logging, metrics, and alerting to ensure platform health and integration reliability.
- Cost Management: Monitor and optimize platform costs effectively using AWS tools such as CloudWatch Budgets.
- Security & Governance: Implement secure authentication and authorization patterns, along with technical guardrails to support AI governance, data privacy, and the principle of least privilege access.
Required Experience & Skills
- Education: Bachelor’s degree in Computer Science, Engineering, or a related technical field; or equivalent practical experience.
- Certifications: Preferred: AWS Solutions Architect Associate or Professional OR Kubernetes/CNCF certifications.
- Experience:
- 5+ years in software, platform, or infrastructure engineering.
- 2+ years in cloud/platform/SRE, MLOps, or data/AI infrastructure roles.
- Proven track record of delivering production systems that integrate multiple services via APIs.
- Technical Skills:
- Strong programming proficiency in at least one of: Python, TypeScript/JavaScript, Go, or Java.
- Practical experience with Amazon Web Services (AWS).
- Hands-on experience with Infrastructure as Code (IaC) tools such as Terraform or AWS CDK.
- Experience with containerization and orchestration technologies like Docker, ECS Fargate, and/or EKS/Kubernetes.
- Familiarity with CI/CD tooling (AWS CodePipeline, GitHub Actions, GitLab CI, or similar).
- Experience configuring observability tools like CloudWatch and OpenTelemetry (or equivalents).
- Experience in monitoring and optimizing cloud costs using tools like CloudWatch Budgets or equivalent.
- AI / LLM Skills:
- Practical experience with enterprise search, LLM/GPT APIs, or Work AI platforms (e.g., Glean, Microsoft 365 Copilot, ChatGPT Enterprise).
- Understanding of key AI concepts such as RAG, vector search, and prompt engineering, or a demonstrated ability to learn these concepts quickly.
- Collaboration & Communication:
- Strong problem-solving and debugging skills across distributed systems.
- Excellent ability to communicate clearly and collaborate effectively with product, security, data, and application teams.
Nice to Have
- Direct experience with Glean or similar Work AI/enterprise search platforms.
- Experience building internal developer platforms, marketplaces, or app stores.
- Experience working in regulated or security-sensitive environments.
Why Ahead: Ahead fosters a diverse and inclusive work environment, valuing contributions from individuals with varied backgrounds and experiences. We invest in our employees' growth through state-of-the-art technology labs, cross-departmental training, and support for certifications and credentials.
Company
Ahead
Ahead is a leading platform provider focused on empowering digital businesses. By integrating advancements in cloud infrastructure, automation, analytics, and software delivery, we enable enterprises ...