AI Engineer

Position:

Job Type:

Location:

About the Role:

drive the design, deployment, and continuous improvement of agentic AI applications

Key Responsibilities:

• Agent Architecture & Orchestration:

• Design and implement agent pipelines using frameworks like LangGraph, Google ADK, CrewAI, etc.
• Integrate external APIs, custom tool calls, and endpoints.

• Prompt Engineering & Feedback Loops:

• Develop and optimize domain-specific prompt templates.
• Embed complex business logic into multi-step workflows.
• Build user-feedback pipelines to retrain, fine-tune, and adjust agent behavior.

• Secure Deployments:

• Containerize and deploy LLMs securely on Azure Cloud (AKS/Azure ML).
• Manage CI/CD pipelines and environment provisioning (Terraform).

• Observability & Evaluations:

• Monitor agent performance, latency, failures, and error handling.
• Implement agent evaluation frameworks (RAGAS, DeepEval, Langfuse) and track metrics over time.

• Collaboration:

• Work closely with backend and data engineers to deliver end-to-end solutions.
• Document architectures, runbooks, and lessons learned from iterations.

Required Skills & Experience:

• 4–7 years in Data Science / ML Engineering (including computer vision), with 12+ months of LLM production experience.
• Hands-on experience with agentic AI frameworks; LangGraph experience preferred.
• Strong prompt engineering skills in complex, domain-specific contexts.
• Proven experience deploying models securely in cloud environments (Azure preferred).
• Familiarity with containerization (Docker, Kubernetes) and serverless computing.
• Experience with observability & evaluation platforms (Langfuse, LangSmith).
• Strong Python coding skills and experience with REST/gRPC API integrations.
• Ability to translate complex business logic into detailed agent workflows.

Preferred / Nice-to-Have:

• Fine-tuning open-source models (DeepSeek, Llama, Mistral) for domain-specific tasks.
• Prototyping RL-based improvements or RL-as-a-Service experiments.
• Prior production exposure to real estate or construction data science applications.

Why Join Us:

• Fast-growing, revenue-generating proptech startup.
• Real-world enterprise production use cases for steep learning.
• Remote-first, with quarterly meet-ups.
• Exposure to multiple markets and diverse clients.

Note:

As an early-stage startup, candidates are expected to wear multiple hats, work beyond their comfort zone, and have direct impact in production. Only applications submitted through the official channel will be considered.