Artificial Intelligence Engineer

About the Role

hands-on AI Engineer

high-impact early-stage role

Key Responsibilities

Agent Architecture & Orchestration

• Design and implement agent pipelines using frameworks such as

  LangGraph, Google ADK, or CrewAI

  .
• Integrate

  external APIs, custom tool calls, and data endpoints

  into agent workflows.

Prompt Engineering & Feedback Loops

• Develop, iterate, and optimize

  domain-specific prompt templates

  for multi-step reasoning.
• Embed business logic into agent workflows and establish

  user-feedback loops

  for continuous improvement.

Secure Deployment

• Containerize and deploy LLMs securely on

  Azure Cloud (AKS / Azure ML)

  .
• Manage

  CI/CD pipelines

  for model updates and environment provisioning using

  Terraform

  .

Observability & Evaluations

• Build

  monitoring and logging systems

  for agent performance, latency, and error handling.
• Implement evaluation frameworks (e.g.,

  RAGAS, DeepEval, Langfuse

  ) to track quality over time.

Collaboration

• Partner with backend and data engineering teams for end-to-end product delivery.
• Document architectures, workflows, and iteration learnings for continuous knowledge sharing.

Required Skills & Experience

• 4–7 years

  in Data Science or ML Engineering, with

  12+ months of hands-on LLM production experience

  .
• Proficiency in

  agentic AI frameworks

  (LangGraph preferred).
• Expertise in

  prompt engineering

  for complex, domain-specific use cases.
• Proven experience deploying AI systems in

  Azure Cloud environments

  .
• Strong knowledge of

  Docker, Kubernetes

  , and secure LLM deployment practices.
• Familiarity with

  observability platforms

  (Langfuse, LangSmith, etc.).
• Strong programming skills in

  Python

  , including

  REST/gRPC API integration

  .
• Ability to translate business logic into structured, automated agent workflows.

Nice to Have

• Experience

  fine-tuning open-source models

  (Llama, Mistral, DeepSeek) for narrow domains.
• Exposure to

  RL-based optimization

  or RL-as-a-Service experimentation.
• Prior experience deploying

  data science applications

  within the

  real estate or construction

  industries.

Why Join

• Work in a

  fast-growing, revenue-generating PropTech startup

  .
• Gain

  hands-on exposure

  to real-world, enterprise-level AI deployments.

• Remote-first culture

  with quarterly team meet-ups.
• Collaborate across

  multi-market client ecosystems

  .
• Direct impact on production systems from day one.

Pro5 is a global platform helping thousands of vetted professionals get hired by top employers. See what others say on our public Google Reviews and learn how we keep your data safe in our Trust Center.