Agentic AI / Orchestration Lead

Tekskills Inc.; Dadri; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

Tekskills Inc. in India seeks an experienced Agentic AI Orchestration Lead with 10+ years in enterprise technology, software engineering, solution architecture and AI‑driven digital transformation to govern and optimize multi‑agent ecosystems.

You will design scalable architectures, establish governance, CI/CD pipelines for AI agents, and lead cross‑functional teams to deliver autonomous business workflows.

Qualifications

• 10 years of experience in enterprise technology, software engineering, or solution architecture.
• Proven track record leading AI orchestration and multi-agent ecosystems.
• Experience with AI governance, security, privacy, and compliance.

Responsibilities

• Define enterprise vision and adoption strategy for AI orchestration.
• Design and implement multi-agent architectures and orchestration frameworks.
• Lead platform engineering delivery and CI/CD for AI agents.
• Establish governance, risk, and compliance for autonomous AI.
• Collaborate with business leaders to translate requirements into AI solutions.
• Mentor AI architects and engineering teams.

Skills

Strategic thinking

AI architectures

Leadership

Cross-functional collaboration

Tools

LangGraph

Semantic Kernel

AutoGen

CrewAI

OpenAI Agents

Job description

Essential Skills:

We are seeking an experienced and visionary Agentic AI Orchestration Lead with 10 years of experience in enterprise technology| software engineering| solution architecture| and AI-driven digital transformation. The ideal candidate will lead the design| implementation| governance| and optimization of multi-agent AI ecosystems that enable autonomous business processes| intelligent decision-making| and scalable enterprise AI adoption

Role Descriptions:

• Strategic Leadership Define the enterprise vision| roadmap| and adoption strategy for Agentic AI and AI orchestration platforms.Establish best practices| standards| governance frameworks| and operating models for AI agents.Drive enterprise-wide AI transformation initiatives and identify high-value automation opportunities.Partner with business and technology leadership to align AI investments with organizational goals.
• AI Agent Architecture Orchestration Design and implement multi-agent architectures involving planner| coordinator| executor| reviewer| and specialist agents.Lead development of orchestration frameworks using technologies such as LangGraph| Semantic Kernel| AutoGen| CrewAI| OpenAI Agents| or similar platforms.Define agent communication patterns| memory management| context sharing| workflow execution| and task delegation strategies.Architect reusable agent services| tools| APIs| and orchestration components.
• Platform Engineering Delivery Lead development and deployment of production-grade AI agents and autonomous workflows.Establish CICD pipelines| testing frameworks| and observability mechanisms for AI systems.Ensure scalability| resilience| security| and performance across AI platforms.Guide engineering teams in implementing AI-powered solutions and enterprise integrations.
• Governance| Risk Compliance Establish AI governance processes covering security| privacy| explainability| and responsible AI practices.Define monitoring| auditing| and evaluation frameworks for autonomous agents.Ensure compliance with enterprise architecture standards and regulatory requirements.Mitigate risks related to hallucinations| data leakage| prompt injection| and model drift.
• Stakeholder Management Innovation Collaborate with business leaders to translate complex requirements into AI-driven solutions.Conduct architecture reviews| proof-of-concepts| and innovation workshops.Evaluate emerging AI tools| models| frameworks| and orchestration technologies.Promote AI adoption through mentoring| training| and organizational change management.
• Team Leadership Lead and mentor AI architects| engineers| prompt engineers| and platform teams.Establish engineering standards| development guidelines| and quality gates.Drive continuous improvement| knowledge sharing| and innovation across AI initiatives.Foster a culture of experimentation while maintaining enterprise-grade controls.