Senior AI Engineer - Agentic AI & Generative AI
Senior AI Engineer - Agentic AI & Generative AI
Posted 11 days ago
SENIORITY
Senior
About the role
- Competitive compensation, including base pay and annual incentive
- Comprehensive health and life insurance and well-being benefits, based on location
- Pension / Retirement benefits
- Build Enterprise AI Solutions
- Design, develop, test, and deploy Generative AI and Agentic AI applications using Amazon Bedrock, AWS, and related AI technologies.
- Build intelligent AI agents and multi-agent systems that automate and enhance business workflows.
- Develop scalable AI-powered solutions that integrate seamlessly with enterprise applications and platforms.
- Design Agentic Architectures
- Design and implement agent orchestration patterns, including: Supervisor and coordinator agents
- Specialized task agents
- Routing and decisioning frameworks
- Context and memory management
- Workflow execution and monitoring
- Build multi-step reasoning workflows that effectively combine LLM intelligence with enterprise systems and business processes.
- Develop AI Integrations
- Integrate AI agents with: REST APIsEnterprise applications
- Internal platforms and services
- Databases and data platforms
- External tools and third-party systems
- Create secure and reusable tools, APIs, and integration layers that enable agent interaction with enterprise systems.
- Implement Knowledge-Driven AIDesign and deliver Retrieval-Augmented Generation (RAG) solutions using enterprise documents, structured data, and knowledge repositories.
- Implement embeddings, vector search, document retrieval, and knowledge-grounding strategies to improve AI accuracy and business outcomes.
- Select and leverage appropriate foundation models based on business and technical requirements.
- 6-8 years of hands-on experience in Software Engineering, AI Engineering, Data Engineering, or related technical disciplines.
- Demonstrated success delivering production-grade AI, Machine Learning, or Generative AI solutions.
- Experience translating business use cases into scalable AI-enabled applications.
- Talent Needed for SuccessAI & Software Engineering
- Strong hands-on programming expertise in Python.
- Experience developing and deploying Generative AI and LLM-powered applications.
- Strong experience with Amazon Bedrock and AWS-based AI services.
- Experience designing and implementing AI agents and agentic workflows.
- Strong understanding of: Agent orchestration
- Multi-agent architectures
- Tool/function calling
- Agent memory
- Context management
- Prompt engineeringAI & Data Platforms
- Hands-on experience with: Retrieval-Augmented Generation (RAG)
- Experience with Agentic AI frameworks such as: CrewAILangGraphAutoGenSimilar orchestration frameworks
- Experience with Model Context Protocol (MCP).Experience building complex multi-agent collaboration systems.
- Experience with AI evaluation, monitoring, and observability frameworks.
- Experience using Kiro or other AI-assisted development tools.
- Experience with OpenShift (OCP), containers, and cloud-native deployments.
- Experience implementing CI/CD pipelines and DevOps practices for AI applications.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
