AI Engineer - Generative and Agentic AI

Job Summary

As an AI Engineer focused on Generative and Agentic AI, you will design, build, deploy, and operate production-ready AI systems, taking ideas from early prototypes through to reliable, enterprise-grade solutions. This role involves a hands-on approach with real customer and internal use cases, owning the full lifecycle from design and orchestration to deployment, monitoring, and continuous improvement.

Responsibilities

• Generative & Agentic AI Development

  • Design and build LLM-based systems using:
    • Retrieval Augmented Generation (RAG)
    • Embeddings and vector search
    • Prompt engineering and prompt optimization
    • Function calling and tool usage
    • Agentic and multi-agent workflows
  • Develop AI systems that integrate LLMs with REST APIs, enterprise systems, data platforms, and workflows.
  • Apply LLM evaluation techniques to assess quality, reliability, safety, and performance.

• End-to-End AI Engineering

  • Own the full lifecycle of AI solutions—from prototype to production.
  • Build, deploy, and operate AI workloads in AWS environments.
  • Ensure production readiness with a focus on scalability, reliability, performance, security, and cost optimization.
  • Implement CI/CD pipelines, automated testing, and versioning for AI systems.

• Engineering Excellence & Operations

  • Apply strong software engineering and distributed systems principles to AI development.
  • Implement observability practices including logs, metrics, traces, and alerts.
  • Monitor model behavior, system health, latency, and failures in production.
  • Contribute to responsible AI practices, governance, and quality standards.

• Collaboration & Enablement

  • Work closely with other AI engineers, data scientists, platform teams, and business stakeholders.
  • Contribute to building and scaling AI platforms and reusable components.
  • Support low-code / Copilot / Flow-style solutions where appropriate.
  • Share knowledge and mentor junior engineers on Generative and Agentic AI best practices.

Qualifications

• Technical Skills

  • Proficient in Python
  • Experience with REST APIs
  • Knowledge of CI/CD pipelines
  • Familiarity with automated testing
  • Understanding of distributed systems fundamentals

• Generative & Agentic AI Skills

  • Strong grasp of Generative AI concepts
  • Experience with LLM-based systems
  • Knowledge of Agentic and multi-agent workflows
  • Proficient in Retrieval Augmented Generation (RAG)
  • Familiarity with embeddings and vector databases
  • Skills in prompt engineering
  • Experience in LLM evaluation

• Cloud & AI Platforms

  • Familiarity with AWS Bedrock
  • Experience with Amazon SageMaker

• Production & Operations

  • Knowledge of observability (logs, metrics, tracing, alerts)
  • Experience in monitoring and performance tuning

Preferred Skills

• Experience supporting enterprise AI platforms or shared AI services.
• Exposure to Copilot-style or workflow automation solutions.
• Familiarity with Responsible AI principles and governance.
• Experience working with cross-functional or client-facing teams.

Experience

• A minimum of 5-7 years of relevant experience in AI engineering and development.