Artificial Intelligence Engineering Lead

Provoke Solutions is hiring an Artificial Intelligence Engineering Lead to build and extend an AI infrastructure platform that integrates AI agents into engineering workflows. The role develops event-driven AWS services, connects Amazon Bedrock agents to GitLab CI/CD, and implements security, cost management, observability, and reliability capabilities.

Responsibilities

• Build and maintain AWS Lambda functions that orchestrate AI agents, including routing, queue management, and Amazon Bedrock Agent invocation
• Develop event-driven architectures using Amazon SQS, EventBridge, and other AWS services
• Create modular, reusable platform components that support new agents, tools, and triggers without requiring changes to unrelated services
• Integrate AI agent capabilities into GitLab CI/CD pipelines using .gitlab-ci.yml configurations
• Build pipeline stages that provide agents with branch, code-diff, and test context
• Enable agents to generate artifacts, return execution results, and determine whether downstream pipeline stages proceed based on defined success or failure criteria
• Develop reusable, AWS Lambda-backed Action Groups that allow agents to interact with approved tools and services
• Configure Amazon Bedrock Knowledge Bases using Amazon S3 and Amazon OpenSearch Service to provide agents with relevant organizational context
• Design extensible integrations that support shared knowledge, retrieval, and agent capabilities across engineering teams
• Implement Amazon Bedrock Guardrails, including input and output filtering, sensitive-data protection, and content restrictions
• Apply least-privilege IAM policies, secure secrets management, input validation, and agent-specific permission boundaries
• Identify and mitigate risks associated with prompt injection, unauthorized tool access, and sensitive-data exposure in LLM-powered workflows
• Implement token and cost management controls, including model selection, intelligent routing, semantic caching, and context-window management
• Contribute to an LLM gateway that supports efficient model usage and cost-aware execution
• Monitor usage patterns and identify opportunities to improve platform performance and resource efficiency
• Build CloudWatch dashboards, structured logging, metrics, and tracing capabilities
• Maintain audit trails for agent executions, including inputs, outputs, decisions, token consumption, and associated costs, with appropriate security and data-retention controls
• Troubleshoot production issues and improve the reliability, debuggability, and transparency of agent workflows

Preferred

• Experience with application security and code analysis tools, including SAST, DAST, or SCA
• Experience building internal developer platforms, engineering tools, or shared services used by multiple development teams
• Familiarity with Amazon Bedrock AgentCore or comparable agent development and runtime frameworks
• Experience implementing LLM gateways, model routing, semantic caching, or token-usage optimization
• Understanding of retrieval-augmented generation (RAG), knowledge retrieval, and enterprise AI integrations
• Experience designing secure, scalable, event-driven architectures in AWS
• Application Security
• Code Analysis Tools
• SAST
• DAST
• SCA
• Internal Developer Platforms
• Engineering Tools
• Agent Development Frameworks
• Agent Runtime Frameworks
• Amazon Bedrock AgentCore
• LLM Gateways
• Model Routing
• Semantic Caching
• Token Usage Optimization
• Retrieval-Augmented Generation (RAG)
• Knowledge Retrieval
• Enterprise AI Integration
• AWS
• Secure Architecture Design
• Scalable Architecture Design
• Event-Driven Architecture

Benefits

• Remote (United States)

Company

• End-to-end technology services and AI-driven software development
• The Colony, Texas, USA
• http://www.provokesolutions.com/
• Founded in 2001
• 51-200 employees

Qualifications

• 3–5 years of professional software engineering experience
• Strong Python development skills, including experience using the AWS SDK for Python (Boto3) to build production-grade Lambda functions and event-driven services
• Hands-on experience with AWS services, including Lambda, API Gateway, SQS, EventBridge, IAM, Secrets Manager, and CloudWatch
• Practical experience with Amazon Bedrock, specifically Agents, Action Groups, Knowledge Bases, and Guardrails
• Experience integrating LLM APIs into applications, such as Amazon Bedrock, OpenAI, Anthropic, or comparable platforms
• Familiarity with CI/CD platforms, preferably GitLab CI/CD, including pipeline configuration and automation
• Understanding of cloud security principles, including least-privilege access, secure credential handling, input validation, and data protection
• Awareness of LLM-specific security risks, including prompt injection and potential data leakage
• Experience implementing observability practices such as structured logging, metrics, tracing, and production troubleshooting
• Ability to develop modular, maintainable services with clear interfaces and well-defined responsibilities
• Candidates must be authorized to work in the U.S. without VISA sponsorship
• Experience with application security and code analysis tools, including SAST, DAST, or SCA
• Experience building internal developer platforms, engineering tools, or shared services used by multiple development teams
• Familiarity with Amazon Bedrock AgentCore or comparable agent development and runtime frameworks
• Experience implementing LLM gateways, model routing, semantic caching, or token-usage optimization
• Understanding of retrieval-augmented generation (RAG), knowledge retrieval, and enterprise AI integrations
• Experience designing secure, scalable, event-driven architectures in AWS
• 3–5 years of professional software engineering experience.

Required skills

• AWS IAM, AWS Lambda, AWS Secrets Manager, Amazon API Gateway, Amazon Bedrock, Amazon CloudWatch, Amazon EventBridge, Amazon SQS, Boto3, Cloud Security, Event-Driven Architecture, GitLab CI/CD, LLM API Integration, LLM Security, Python, Retrieval-Augmented Generation (RAG), SAST/DAST/SCA

Experience

• 3-5 years