Agentic AI Platform Engineer

Job Title:            Agentic AI Platform Engineer

Location:           United States (Remote)

Hire Type:          Contract (6 months+)

About the Role:

Our client is looking for a skilled Agentic AI Platform Engineer to help build and scale a centralized agentic AI ecosystem that enables engineering teams to seamlessly integrate AI-driven workflows into their development lifecycle.

In this role, you will contribute to the development of secure, scalable, and observable AI orchestration services that integrate with CI/CD pipelines and cloud-native infrastructure. You will work on enabling reusable AI capabilities that can be adopted across teams without requiring custom implementations each time.

Key Responsibilities:

• Develop and maintain orchestration services using AWS Lambda, SQS, and event-driven architectures to manage AI agent workflows.
• Build integrations with GitLab CI/CD pipelines, enabling AI-powered automation within build and deployment stages.
• Create reusable serverless tools and shared service components that can be leveraged by multiple engineering teams.
• Design and implement AI knowledge repositories using AWS Bedrock Knowledge Bases, OpenSearch, and S3 to improve contextual reasoning for AI agents.
• Implement governance and security controls including guardrails, sensitive-data filtering, access restrictions, and prompt validation mechanisms.
• Optimize AI usage through model routing, semantic caching, token management, and cost-aware processing strategies.
• Establish observability and monitoring standards using CloudWatch, centralized logging, tracing, and audit reporting for AI interactions and platform usage.
• Collaborate with platform and engineering teams to improve extensibility, scalability, and developer experience.

Required Skills & Experience:

• 3–5 years of professional software engineering experience.
• Strong proficiency in Python and AWS SDKs for building production-grade serverless applications.
• Hands-on experience with AWS services such as Lambda, API Gateway, SQS, EventBridge, IAM, Secrets Manager, and CloudWatch.
• Experience working with Amazon Bedrock, including Agents, Action Groups, Knowledge Bases, and Guardrails.
• Practical experience integrating Large Language Model APIs such as Bedrock, OpenAI, Anthropic, or similar platforms.
• Good understanding of CI/CD concepts and hands-on exposure to GitLab CI pipelines.
• Strong awareness of application security, including IAM best practices, secrets handling, prompt injection prevention, and secure AI workflow design.
• Experience implementing logging, tracing, monitoring, and debugging solutions in distributed systems.

Preferred Qualifications:

• Experience with vector databases, retrieval-augmented generation (RAG), embeddings, or OpenSearch.
• Familiarity with AI cost optimization strategies including semantic caching, inference routing, and token utilization tracking.
• Experience building internal developer platforms, automation tooling, or reusable engineering frameworks.
• Exposure to agentic AI frameworks and orchestration patterns.