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.
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