Solution Architect

AlgoLeap Technologies Pvt Ltd.; Hyderabad; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

AlgoLeap Technologies Pvt Ltd. in Hyderabad seeks an experienced Agentic AI Orchestration Lead with 10+ years in enterprise technology, software engineering, solution architecture, and AI-driven digital transformation.

You will lead design, implementation, governance, and optimization of multi-agent AI ecosystems enabling autonomous business processes. The role requires strategic leadership, hands-on architecture, and collaboration with business leadership to drive AI adoption and scalable

Qualifications

• 10+ years of experience in enterprise technology, software engineering or solution architecture.
• Experience leading multi-agent AI ecosystems and autonomous business processes.

Responsibilities

• Define enterprise vision, roadmap, and adoption strategy for Agentic AI and orchestration platforms.
• Architect reusable agent services, tools, APIs, and orchestration components.
• Lead production-grade AI agents delivery, CI/CD pipelines, testing, and observability.
• Establish AI governance, security, privacy, explainability, and responsible AI practices.
• Partner with business and tech leadership to align AI investments with goals.

Skills

AI Agents

Enterprise tech

Software engineering

Solution architecture

AI governance

Job description

Skills: AI Agents

Experience Required: 10 & Above

Location: Hyderabad

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 LeadershipDefine 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 OrchestrationDesign 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 DeliveryLead 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 ComplianceEstablish 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 InnovationCollaborate 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 LeadershipLead 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.