AI Engineer

Drive the design, build, deployment, and continuous improvement of agentic AI applications for the real estate and construction industry. You’ll own end-to-end agent frameworks, architecting tool chains, crafting prompts, integrating data, and running observability and feedback loops to deliver production-grade AI agents. 

Key responsibilities:

• Agent Architecture & Orchestration

• Design and implement agent pipelines using frameworks like LangGraph, Google ADK, CrewAI, etc.
• Wire up external APIs, custom tool calls and endpoint integrations

• Prompt Engineering & Feedback loops

• Develop, iterate, and optimize domain-specific prompt templates at speed
• Embed complex business logic into multi-step prompt 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). Familiarity with secure LLM application deployments in Kubernetes clusters.
• Manage CI/CD for model updates and environment provisioning (Terraform)

• Observability & Evals

• Build monitoring and logging for agent performance, latency, failures and error handling. 
• Implement agent eval frameworks and track metrics over time (RAGAS, DeepEval/ Langfuse, etc.)

• Collaboration

• Partner with backend & data engineers to deliver end-to-end product
• Document architectures, runbooks and learnings from iterations

Required skills and experience:

• 4–7 years in data science (ML engineering/computer vision), with over 12 months of LLM production experience
• Hands-on with agentic AI frameworks; strong preference for LangGraph
• Expert prompt and context engineering skills in complex, domain-specific contexts
• Proven track record deploying models in secure cloud environments. Working experience in the Azure ecosystem is essential. 
• Experience with containerization (Docker, Kubernetes) and serverless compute
• Familiarity with observability & eval platforms (Langfuse/LangSmith)
• Ability to translate nuanced business logic into detailed agent workflows and prompts. 
• Strong coding skills in Python, plus experience with REST/gRPC API integrations

Nice to have skillsets:

• Fine-tuning open source models (DeepSeek/Llama/Mistral) for narrow domain based tasks, ensuring higher overall accuracy & consistency
• Prototyping RL-based improvements or RL-as-a-Service experiments
• Prior production exposure to real estate, construction or manufacturing domains in building and deploying any data science application (not necessarily LLM based)

We are an early-stage startup, so you are expected to wear many hats, working with things out of your comfort zone, but with real and direct impact in production. If you think you are a good fit for this fast-paced environment, please apply on the form. No direct messages, e-mails will be considered please.

Why us?

Fast-growing, revenue-generating startup

Multi-market client exposure

Non-hierarchical environment. Build together, ship together, grow together.

Steep learning opportunities in real world enterprise production use-cases

Remote work with quarterly meet-ups