Agentic Ai Orchestration Lead Tekskills Hyderabad
Building and orchestrating multi-agent AI systems using tools like LangGraph, Semantic Kernel, AutoGen and OpenAI Agents; focused on AI dev/platform work.
About the Role
Lead the design, implementation, governance, and optimization of enterprise-grade multi-agent AI ecosystems to enable autonomous business processes and scalable AI adoption. Drive strategy, platform engineering, risk and compliance, and mentor teams to deliver production-grade AI agents and workflows.
Job Description
Role
Agentic AI Orchestration Lead responsible for defining the enterprise vision, roadmap, and adoption strategy for agentic AI and AI orchestration platforms. The role leads design and implementation of multi-agent architectures and delivery of production-grade autonomous workflows while ensuring governance, compliance, security, and scalability.
Key Responsibilities
- Strategic leadership: define enterprise vision, roadmap, standards, governance frameworks, and operating models for Agentic AI.
- AI agent architecture: design and implement multi-agent architectures (planner, coordinator, executor, reviewer, specialist agents) and define communication, memory, context sharing, workflow execution, and task delegation strategies.
- Orchestration platform design: lead development of orchestration frameworks and reusable agent services, tools, APIs, and components.
- Platform engineering & delivery: lead development and deployment of production-grade AI agents and autonomous workflows; establish CI/CD pipelines, testing frameworks, and observability; ensure scalability, resilience, security, and performance.
- Governance, risk & compliance: establish AI governance for security, privacy, explainability, monitoring, auditing, and evaluation; mitigate hallucinations, data leakage, prompt injection, and model drift.
- Stakeholder management & innovation: collaborate with business and technology leaders, run architecture reviews, POCs, and innovation workshops; evaluate emerging tools and frameworks.
- Team leadership: lead and mentor AI architects, engineers, and prompt engineers; set engineering standards, quality gates, and promote knowledge sharing.
Requirements
- 10 years of experience in enterprise technology, software engineering, solution architecture, or AI-driven digital transformation.
- Proven experience designing and implementing multi-agent AI systems and orchestration frameworks.
- Hands-on experience with orchestration platforms and agent tooling (examples called out: LangGraph, Semantic Kernel, AutoGen, CrewAI, OpenAI Agents) or similar technologies.
- Strong platform engineering skills: CI/CD pipelines, testing frameworks, observability, scalability, resilience, security, and performance tuning.
- Experience defining and implementing AI governance, monitoring, auditing, explainability, and responsible AI practices.
- Track record mitigating AI-specific risks such as hallucinations, data leakage, prompt injection, and model drift.
- Strong stakeholder collaboration, architecture review and POC experience, and ability to translate business requirements into AI solutions.
- Leadership experience: mentoring teams, establishing standards, driving adoption, and managing organizational change.
Notes
- Focus is on enterprise-scale adoption and governance of agentic AI; role emphasizes both technical architecture and organizational change management.