Principal/ Senior AI/LLM Solution Engineer

Job Description

We are looking for an AI Solution Engineer with a strong foundation in large language models (LLMs), prompt design, and system integration — someone who can go beyond prompt tuning to design, build, and operate practical AI Agent systems that enhance and automate back-office workflows. Candidates for this position are expected to join the development team, understand the product and continuously research, and recommend AI features to realize AI product vision.

• Design and develop AI or AI Agent engines to integrate sophisticated features into a workflow application SaaS for automating and enhancing back-office operations using LLMs.
• Develop and iterate on high-quality prompts, prompt-chaining strategies, and evaluation pipelines.
• Monitor agent behavior and system metrics to identify and mitigate hallucinations, performance degradation, or edge cases.
• Evangelize and integrate tools, workflows, and development cultures to support rapid and responsible AI feature development.
• Collaborate with backend, frontend, and infrastructure teams for seamless integration and delivery.
• Share best practices with team members for prompt engineering, LLM integration, cloud AI tools utilization, and evaluation methodologies.
• Take technical ownership of AI initiatives, leading cross-functional collaboration (BE/FE/AI/SRE), and driving system-level decisions

Requirements

• Technical
  • Must have
    • 5+ years of experience with Python (or Golang as an alternative).
    • 5+ years of Web application development.
    • Practical experience designing and optimizing prompts for LLMs in production environments.
    • Good understandings of:
      • Backend development (e.g., web frameworks, databases).
      • Cloud infrastructure (e.g., Azure, AWS, Terraform, serverless architecture).
      • MLOps pipeline.
    • Experience in:
      • Architectural design for multi-agent orchestration.
      • LLM orchestration frameworks like AutoGen, LangChain, and LlamaIndex.
      • RAG architecture and vector stores.
      • Integrating AI services from platforms like Azure AI Foundry, AWS Bedrock, or GCP Vertex AI.
  • Nice to Have
    • Basic understanding of frontend development (e.g., TypeScript/React).
    • Familiarity with fine-tuning or instruction-tuning LLM models.
    • Understanding of AI system deployment from a security/compliance standpoint.
    • Exposure to IaC and CI/CD in production systems.
    • Experience in B2B application development.
    • Experience introducing traditional machine learning techniques and related ML pipelines to improve businesses.
• Communication
  • Strong English communication, both verbal and written.
  • Experience in leading a project as a team leader.
  • Experience in educating team members.
  • Strong sense of ownership.