Overview
Skills
Job Details
Key Responsibilities
- Design and oversee the architecture of AI-powered applications and platforms.
- Collaborate with business and engineering teams to integrate AI Agents into production systems.
- Define and enforce architectural standards, patterns, and best practices for AI systems.
- Evaluate emerging AI technologies and recommend adoption strategies.
- Lead modernization initiatives including cloud migration and microservices adoption.
- Ensure scalability, performance, and security of AI-enabled solutions.
- Provide technical leadership and mentorship to software engineers.
- Partner with stakeholders to align AI architecture with business goals.
- Architect scalable agentic AI frameworks using LangGraph, LangMem, and custom agent orchestration.
- Design and implement advanced RAG architectures including hybrid search, query routing, and contextual retrieval.
- Establish multi-agent systems with Agent-to-Agent (A2A) communication protocols and Model Context Protocol (MCP).
- Architect Small Language Model (SLM) integration for specialized tasks and cost optimization.
- Establish comprehensive monitoring, observability, and performance optimization strategies.
- Scope, manage, and drive complex GenAI projects and programs to successful completion.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, or related field.
- 5+ years of experience in software architecture and system design.
- Minimum 4+ years of experience conceptualizing and architecting the target environment for AI solutions
- Proven experience with AI technologies such as Azure OpenAI, Agentic Framework, AI Plugins, Content Understanding, DocIntelligence, Chunking Strategies, Indexing and Vectorization etc.
- Strong knowledge of cloud platforms (Azure, AWS, Google Cloud Platform) and containerization (Docker, Kubernetes).
- Expertise in .Net programming languages.
- Familiarity MLOps practices
Preferred Skills
- Experience with large language models (LLMs) and generative AI.
- Knowledge of enterprise architecture frameworks.
- Understanding of data privacy, ethics, and responsible AI principles.
- Excellent communication and stakeholder management skills.
- Certifications in AI technologies.