
Technical Lead – Agentic AI Systems
2 weeks ago
We are seeking a highly skilled and visionary Technical Lead to spearhead the design, development, and deployment of agentic AI systems. This role demands deep technical expertise in AI architecture, LLMs, and agent frameworks, along with a strategic mindset to align AI initiatives with business goals. The ideal candidate will have hands-on experience with cutting-edge AI tools and frameworks, and a passion for building scalable, intelligent systems that drive enterprise transformation.
Key Responsibilities:
Technical Leadership & Architecture · Lead the end-to-end design and deployment of agentic AI systems:
·Define and evolve AI system architecture, ensuring alignment with enterprise infrastructure and scalability requirements.
Select and implement appropriate frameworks such as LangGraph, AutoGen, CrewAI, LlamaIndex, and others.
Stakeholder Collaboration
Collaborate with cross-functional teams and stakeholders to align AI solutions with business objectives.
Translate business needs into technical requirements and AI capabilities.
System Integration & Deployment
Ensure seamless integration of agentic AI systems into existing enterprise platforms.
Define and execute strategies for deployment, operationalization, and lifecycle management of AI agents.
Performance Optimization & Monitoring
Design and implement monitoring and observability solutions for AI agents.
- Optimize performance, latency, and scalability of deployed systems.
Implement feedback loops and evaluation frameworks to continuously improve agent performance.
Evaluation & Strategy
Define and apply strategies for agent performance evaluation and LLM benchmarking.
- Stay updated with the latest advancements in LLMs, agent frameworks, and orchestration tools. Required Skills & Qualifications:
- Proven experience in implementing AI solutions for real-world enterprise problems.
Requirements
- Strong expertise in AI system architecture and design.
- Deep practical knowledge of Large Language Models (LLMs), Machine Learning (ML), and Agent Development.
- Hands-on experience with LLM platforms such as Gemini, GPT, LLaMA2, Mistral.
- Proficiency in agentic AI frameworks: LangGraph, Google ADK, AutoGen, CrewAI, and orchestration tools.
- Familiarity with MCP (Multi-Agent Communication Protocols) and agent-to-agent communication.
- Experience with LLM evaluation techniques and agent performance metrics.
- Strong problem-solving skills and ability to work in a fast-paced, collaborative environment. Preferred Qualifications: · Experience working in oAshore delivery models.
- Exposure to enterprise-grade AI deployments and cloud-native architectures.
- Familiarity with DevOps/MLOps practices for AI systems.
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