Original job description
Bachelors or Masters degree in Computer Science, Artificial Intelligence, Engineering, or related discipline.
12+ years of software engineering experience, including 5+ years designing and building enterprise AI/ML platforms.
Proven experience architecting and delivering large-scale AI solutions, Agentic AI systems, AI platforms, or multi-agent frameworks in enterprise environments.
Deep understanding of the Agentic AI ecosystem including agent orchestration, planning, reasoning, tool calling, memory management, retrieval systems, and autonomous workflows.
Hands-on expertise building AI applications using frameworks and platforms such as Google ADK, LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, or similar agentic frameworks.
Strong experience designing scalable orchestration layers, tool libraries, context management frameworks, observability solutions, and governance controls for AI systems.
Expertise in Retrieval-Augmented Generation (RAG), vector databases, embeddings, enterprise knowledge systems, and document intelligence platforms.
Experience designing extensible and reusable AI platform architectures capable of supporting multiple business use cases and domains.
Strong software engineering background in cloud-native architectures, distributed systems, APIs, microservices, and platform engineering.
Deep understanding of AI observability, monitoring, evaluation frameworks, model governance, security, and responsible AI principles.
Exceptional communication and stakeholder management skills with the ability to influence senior technology leaders and architects.
Strong understanding of Agile, Waterfall, and Hybrid delivery methodologies.
More about this job
Responsibilities
Architect and deliver enterprise-scale Agentic AI systems, AI platforms, and multi-agent solutions, including reusable orchestration, tool, context-management, observability, and governance capabilities. Design extensible AI platform architectures that support diverse business domains while addressing scalability, security, monitoring, evaluation, and responsible AI.
Requirements
Requires a bachelor's or master's degree in a relevant discipline and 12+ years of software engineering experience, including 5+ years designing and building enterprise AI/ML platforms. Candidates should have deep expertise in agentic frameworks, RAG, enterprise AI architecture, cloud-native and distributed systems, governance, and stakeholder communication.
Skills
- Agentic AI Architecture
- AI/ML Platforms
- Agent Orchestration
- Planning And Reasoning
- Tool Calling
- Memory Management
- Retrieval-Augmented Generation
- Vector Databases
- Cloud-Native Architecture
- Distributed Systems
- APIs And Microservices
- AI Observability
- Model Governance
- Responsible AI
- Stakeholder Management
- Agile Delivery
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Management & Leadership
Keywords
- Agentic AI
- Google ADK
- LangGraph
- LangChain
- Semantic Kernel
- CrewAI
- AutoGen
- AI/ML Platforms
- Multi-Agent Frameworks
- Agent Orchestration
- Retrieval-Augmented Generation
- Vector Databases
- Embeddings
- Enterprise Knowledge Systems
- Document Intelligence
- Cloud-Native Architecture
- Distributed Systems
- APIs
- Microservices
- Platform Engineering
- AI Observability
- Evaluation Frameworks
- Model Governance
- AI Security
- Responsible AI
- Agile
- Waterfall
- Hybrid Delivery
