GenAI Adoption Lead
Indexed description
Our Client is a global leader in corporate brand protection and domain management, serving Fortune 500 and large enterprises with domain registration, online brand monitoring, and anti-counterfeiting services.
Project Description:
Alongside the consolidation of its legacy client portals into a single modern platform, the Client is investing in internal AI capabilities to accelerate engineering and operations. This role focuses on building internal AI tools, agentic workflows, and engineering tooling - leveraging AWS Bedrock and a solid MLOps foundation.
Requirements:
- 5+ years of commercial software engineering experience, with a strong focus on AI/ML engineering
- Hands-on experience with AWS Bedrock — foundation models, agents, and knowledge bases
- Solid MLOps experience — model deployment, monitoring, pipelines, evaluation, and lifecycle management
- Proven experience building AI agents, agentic workflows, or LLM-powered internal tools
- Strong Python skills for AI/ML development and tooling
- Experience with RAG, prompt engineering, and vector databases
- Familiarity with LLM/agent frameworks (e.g. LangChain, LlamaIndex, or comparable)
- Hands-on experience with AWS services beyond Bedrock
- Strong understanding of testing and evaluation practices for AI systems
- Familiarity with modern CI/CD pipelines and Git workflows
- Ability to work in a distributed, multi-timezone team (US / UK / Brazil), with meaningful US Mountain Time overlap preferred
- Excellent English communication skills
- Experience working in Agile / Scrum / Kanban
- Experience with AI-assisted development tools (Copilot, Claude, Cursor)
- Experience embedding AI into existing engineering workflows and developer tooling
- Background in SaaS, multi-tenant platforms, or large-scale B2B portals
- Familiarity with the PHP / Laravel ecosystem (useful for tooling that integrates with the platform)
- Design, develop, and deliver internal AI tools and agentic workflows using AWS Bedrock
- Build and maintain MLOps pipelines for deployment, monitoring, and evaluation of AI capabilities
- Develop engineering tooling that improves developer productivity and quality across the team
- Contribute to architectural discussions and technical decisions for the AI workstream alongside the Tech Lead
- Implement RAG, prompt engineering, and evaluation frameworks to ensure reliable, measurable AI behavior
- Write clean, testable code with appropriate test and evaluation coverage
- Participate in code reviews, sharing knowledge and maintaining quality standards
- Break down user stories into technical tasks; estimate effort during sprint planning
- Troubleshoot issues and contribute to root-cause analysis
- Engage with Client engineering counterparts in US / UK / Brazil on integration points and delivery milestones
- Participate in Agile ceremonies (stand-ups, planning, retros, demos)
- Flexible working format - remote, office-based or flexible
- A competitive salary and good compensation package
- Personalized career growth
- Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
- Active tech communities with regular knowledge sharing
- Education reimbursement
- Memorable anniversary presents
- Corporate events and team buildings
- Other location-specific benefits
- not applicable for freelancers
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