Agentic AI Solutions Architect Manager

Job Location: Pakistan (Remote)

Department: Technology

Type: Full-Time

Working hours: 6 pm – 3 am (US Hours)

Vision: Transforms students’ lives through Innovating workforce development models addressing skillset gaps

Mission: Transforms students’ lives by curating university programs and mapping them to certifications aligned to the emerging job market through apprenticeship and upskilling programs

At EdTech Ventures, we are committed to upholding the following core values:

P*assion |Respect | Accountability | Innovation | Speed | Execution [ PRAISE* ]

Overview:

The Agentic AI Solutions Architect Manager leads the design, integration, and deployment of agentic-AI–driven systems for the EdTech venture’s RAD program. This role combines strategic technical leadership, hands-on architecture development, and cross-functional collaboration to accelerate the delivery of AI-native learning experiences, content automation workflows, and adaptive learning intelligence.

The manager will oversee a team of AI solutions architects and engineers, guiding them to build scalable agentic systems, LLM-enabled pipelines, and modular AI services tailored for rapid prototyping and iterative product delivery.

Responsibilities, include but are not limited to:

AI Architecture & System Design

• Design end-to-end architectures for agentic AI workflows, including planning agents, orchestration layers, tool-use systems, and retrieval augmentation.
• Define modular, reusable AI service components aligned with RAD needs.
• Evaluate and integrate LLMs, vector databases, RL frameworks, and agent frameworks (OpenAI API, LangChain, Microsoft AutoGen, etc.).

2. Technical Leadership & Delivery

• Lead a team of AI architects/engineers in designing and implementing agentic systems.
• Run architecture reviews, technical spikes, and PoC/prototype cycles.
• Own technical decisions, ensuring quality, reliability, and performance of AI systems.

3. Stakeholder Collaboration

• Work closely with product, learning science, and instructional design teams to translate EdTech needs into AI solutions.
• Provide technical consultations to cross-functional RAD squads and guide them through AI integration.

4. Innovation & R&D

• Evaluate emerging agentic AI patterns (self-reflection, multi-agent coordination, tool governance).
• Develop internal frameworks, templates, and best practices for AI-native product development.
• Advocate for usable, ethical, and pedagogically aligned AI systems.

5. Project & Risk Management

• Track delivery timelines, backlog prioritization, and resource allocation.
• Manage technical risks related to AI hallucination, data governance, bias, and security.

Minimum Qualifications

Education

• At least Bachelor’s degree in Computer Science, AI, Software Engineering, or a related discipline.

Experience & skills

• 10+ years of experience in software engineering, with at least 4–5 years in solutions architecture or technical architecture leadership roles.
• 7+ years in software architecture or AI engineering, 2+ years in LLM-based or agentic AI systems.
• Proven experience leading technical teams in fast-paced environments.
• Expertise in LLM orchestration, agent frameworks, and prompt engineering.
• Strong grasp of data pipelines, cloud infrastructure (AWS/Azure/GCP), and scalable service design.
• Experience building or integrating EdTech, learning analytics, or personalization systems (preferred).

Competency Identifiers

1. AI Systems Design (Agentic, LLM, RAG): Ability to architect complex, AI-native and agentic workflows end-to-end.

2. Multi-Agent Orchestration & Tool Integration: Designing coordinated agent behaviors, tool-use pipelines, and orchestration layers.

3. Modular RAD-Friendly Component Design: Creating reusable AI modules that accelerate rapid prototyping and product iteration.

4. Technical Team Leadership: Leading architects/engineers, driving decisions, and maintaining architecture quality.

5. Technical Spikes & Prototyping: Running fast PoCs to validate AI approaches early in the RAD cycle.

6. AI Safety, Reliability & Governance: Ensuring privacy, safety guardrails, and low-hallucination, responsible AI deployment.

7. Cross-functional Collaboration & Communication: Communicates clearly with non-technical stakeholders and demonstrates partnership mindset.

Key Performance Indicators (KPIs)

• Successful delivery of AI features/prototypes within RAD cycle timelines.
• Reduction in development time through reusable AI modules.
• Accuracy, reliability, and pedagogical alignment of deployed agentic systems.
• Stakeholder satisfaction (product, learning science, engineering).
• Team capability uplift (skills, velocity, architecture quality).

Job Type: Full-time

Work Location: Remote