3+ years hands-on AI/ML or Generative AI experience
Production experience in enterprise-scale AI applications
Experience designing AI architectures and platforms
Strong expertise in Agentic AI and AI agents
Proficient in Azure and related services
Strong development skills in Python and experience with API management
Responsibilities
Design and create advanced multi-agent AI systems for enterprise applications
Develop autonomous AI workflows and orchestration patterns
Build scalable frameworks for agent communication and execution
Create comprehensive API-driven AI services with governance controls
Establish AI governance practices across multiple business domains
Implement observability frameworks and monitor AI execution metrics
Ensure compliance and implement security measures in AI systems
Benefits
Opportunities for professional development and training
Access to cutting-edge technology and resources
Collaborative work environment with cross-functional teams
Flexible work arrangements and work-life balance initiatives
Participation in AI research and innovation projects
Full Job Description
Role Overview
We are seeking a Senior AI Engineer - Agentic AI Platform to design and build enterprise-scale Agentic AI platforms that enable multiple business domains to develop, deploy, monitor, govern, and operate autonomous AI agents.
This role requires strong hands-on experience in Agentic AI, multi-agent orchestration, AI platform architecture, model governance, memory management, observability, cost attribution, and cloud-native AI solutions.
The ideal candidate will have production experience with Azure AI Foundry, Azure OpenAI, LangChain, LangGraph, Python, Azure, vector databases, API gateways, and enterprise AI engineering practices.
Key Responsibilities
Agentic AI Development
Design and develop sophisticated multi-agent AI systems for enterprise use cases.
Build autonomous and semi-autonomous AI workflows.
Implement Supervisor-Worker, Sequential, ReAct, Planner-Executor, Writer-Critic, orchestration, and choreography patterns.
Develop scalable agent communication and execution frameworks.
Build closed-loop workflows with validation, retry, evaluation, and feedback mechanisms.
Enterprise AI Platform Engineering
Build reusable AI platform capabilities for multiple business teams.
Design enterprise AI governance and operational controls.
Develop API-driven AI services supporting rate limiting, quota management, authentication, authorization, audit logging, multi-tenant usage tracking, and cost attribution.
Establish agent onboarding and lifecycle management capabilities.
Multi-Agent Orchestration
Design agent communication using direct calls, event-driven architectures, message queues, and publish-subscribe patterns.
Implement orchestration and choreography-based execution models.
Work with Kafka, Azure Service Bus, Azure Durable Functions, and event-driven workflows.
AI Memory & Knowledge Systems
Design short-term and long-term AI memory architectures.
Implement vector databases, semantic caching, conversation memory, agent state persistence, and RAG.
