Technical Architect

Responsibilities

• Architectural Leadership

  : Design and lead the development of complex, scalable, and resilient technical architectures for our software and AI-driven systems.

• Generative AI Strategy

  : Define the technical roadmap for integrating

  Generative AI

  capabilities into products and services, including model selection, fine-tuning, and deployment strategies.

• Agentic Systems Design

  : Architect and implement multi-agent systems using frameworks like

  Crew AI

  , designing roles, tools, and communication protocols for autonomous and collaborative AI agents.

• MCP Expertise

  : Leverage the

  Model Context Protocol (MCP)

  to architect client-server systems. Design and build

  MCP servers

  to expose data and tools, and develop

  client agents

  that can seamlessly interact with these servers to access context and execute tasks.

• Hands-on Coding

  : Maintain a strong coding presence. You will be responsible for building key components, leading by example in code quality, and conducting technical reviews.

• Client & Stakeholder Communication

  : Serve as a primary technical point of contact for clients. Translate complex technical concepts into clear, concise business solutions and manage expectations throughout the project lifecycle.

• Mentorship and Governance

  : Provide technical guidance and mentorship to development teams, ensuring adherence to best practices, coding standards, and architectural principles.

Required Skills & Qualifications

• Bachelors or Masters degree in Computer Science, Engineering, or a related field.

• 10-15 years

  of experience in software development and technical architecture.

• Extensive hands-on coding experience

  in a major language such as Python, Java, or Go.

• Demonstrated expertise in Generative AI

  , including experience with Large Language Models (LLMs), model APIs (e.g., OpenAI, Anthropic), and concepts like RAG (Retrieval-Augmented Generation).

• In-depth knowledge of agentic frameworks

  , with proven experience in designing and building multi-agent systems, particularly with

  Crew AI

  .

• Practical experience with the Model Context Protocol (MCP)

  , including the design and implementation of both servers and client agents to enable context-aware AI applications.
• Exceptional ability to communicate, present, and negotiate with technical teams and non-technical clients and business stakeholders.
• Strong understanding of software development methodologies (e.g., Agile, DevOps) and experience with CI/CD pipelines.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and architecting cloud-native solutions.