Role overview
- Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or related field.
- 5+ years of experience in software engineering with strong exposure to AI/ML systems.
- Hands-on experience designing agent-based or agentic AI systems.
- Experience with emerging paradigms such as MCPs, A2As or similar agent communication standards.
Strong experience with:
- LLM integration and prompt orchestration
- AI orchestration frameworks and multi-agent systems
- API-driven architectures and microservices
Experience with cloud platforms (preferably AWS ) and container orchestration (Kubernetes).
Strong programming skills in Python (or similar languages).
What you'll work on
Architect & Build Agentic AI Systems
- Design and implement scalable, modular agent-based AI architectures.
- Enable agent-to-agent (A2A) communication and coordination across workflows.
- Develop orchestration layers that manage multi-agent interactions and decision-making.
Conversational AI Development
- Build and enhance a conversational chatbot interface (People Assistant) for employee interactions.
- Ensure natural, context-aware, and transaction-capable conversations.
Enterprise Integration
- Integrate AI systems with platforms such as Workday, ServiceNow, and other HR tools via APIs.
- Leverage Microsoft ecosystem capabilities for enterprise-grade solutions.
AI Platform & Infrastructure
- Deploy and manage AI services using Booking Kubernetes Service (BKS).
- Integrate with AI gateways (e.g., Booking AI Gateway) to connect with open-source and licensed LLMs.
- Ensure reliability, scalability, and performance of AI services in production.
AI Innovation & Use Case Development
- Identify and prototype new AI-driven use cases within People Technology.
- Stay current with advancements in LLMs, agent frameworks, and AI orchestration patterns.
Collaboration & Leadership
- Partner with product managers, HR stakeholders, and engineering teams.
- Provide technical leadership and mentorship to junior engineers.
What we're looking for
- Familiarity with HR enterprise platforms such as Workday and ServiceNow.
- Knowledge of conversational AI design, NLU/NLP systems, and dialogue management.
- Experience working with AI gateways or model routing layers.
- Exposure to security, compliance, and governance in enterprise AI systems.
Tags & focus areas
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