AI Technical Lead / Architect

Job Summary

As an AI Technical Lead / Architect focused on Generative and Agentic AI, you will architect, design, and lead the delivery of production-ready, enterprise-grade AI systems. This role entails taking ideas from early experimentation and prototypes through to scalable, secure, and reliable AI solutions that are utilized by real customers and internal users. You'll focus on building intelligent, agent-based systems capable of reasoning, planning, integrating with tools, and autonomously making decisions at an enterprise scale.

Responsibilities

• Technical Leadership & Architecture

  • Provide technical leadership and architecture for Generative and Agentic AI initiatives.
  • Design end-to-end AI system architectures covering orchestration, data, APIs, security, and deployment.
  • Build LLM-based solutions utilizing Retrieval Augmented Generation (RAG), embeddings, prompt engineering, function calling, and agentic workflows.
  • Ensure production readiness including CI/CD, testing, observability, scalability, security, and cost optimization.
  • Mentor AI engineers and collaborate with business and technology stakeholders.

• Generative & Agentic AI Engineering

  • Design and build LLM-based systems using techniques such as:
    • Retrieval Augmented Generation (RAG)
    • Embeddings and vector search
    • Prompt engineering and optimization
    • Function calling and tool usage
    • Agentic and multi-agent workflows
  • Develop AI systems integrating LLMs with APIs, data platforms, enterprise applications, and workflow engines.
  • Employ modern AI evaluation methods, including automated testing, benchmarking, and qualitative + quantitative LLM evaluation.

• Engineering Excellence & Operations

  • Apply strong software engineering and distributed systems principles in AI development.
  • Design for observability by incorporating logging, metrics, tracing, alerts, and model performance monitoring.
  • Diagnose and resolve production issues related to latency, reliability, data quality, and model behavior.
  • Balance innovation speed with operational excellence and long-term maintainability.

• Collaboration, Enablement & Mentorship

  • Collaborate with business stakeholders to convert real-world problems into AI-driven solutions.
  • Partner with AI engineers, data scientists, and platform teams to enhance delivery.
  • Mentor and coach engineers on Generative AI, Agentic AI, and cloud-native best practices.
  • Support low-code and Copilot/Flow-style solutions where suitable while maintaining architectural integrity.

Qualifications

• Bachelor’s or master’s degree in Computer Science, Engineering, or a related field.
• 10+ years of experience in software engineering.
• Proficiency in:
  • Programming & Engineering:
    • Python
    • REST APIs
    • CI/CD pipelines
    • Automated testing
    • Distributed systems design
  • Generative & Agentic AI:
    • Generative AI and LLM-based systems
    • Agentic and multi-agent workflows
    • Retrieval Augmented Generation (RAG)
    • Embeddings and vector databases
    • Prompt engineering and prompt optimization
    • LLM evaluation and testing strategies
  • Cloud & AI Platforms:
    • Azure OpenAI
    • Azure AI Services
    • AWS Bedrock
    • Amazon SageMaker
  • Production & Operations:
    • Observability (logs, metrics, tracing, alerts)
    • Monitoring and reliability engineering
    • Performance tuning and cost optimization

Preferred Skills

• Experience in leading cross-functional teams.
• Familiarity with DevOps practices and tools.
• Skills in machine learning frameworks such as TensorFlow or PyTorch.

Experience

• Minimum of 10 years of experience in software engineering with a strong focus on AI technologies and solutions.