PositionSummary:
We are looking for a talented Senior Software Engineer – AI & ML to join our growing development team at Property Finder. This role is a blend of hands-on software engineering and applied AI/ML, building intelligent features and platforms that power our core marketplace and internal tools. At Property Finder, we believe in nurturing talent and encouraging creativity and autonomy in a fun, forward-thinking, and positive environment. You’ll work in small, empowered cross-functional teams that take ideas from inception all the way to production, fully tested and monitored, with minimal outside disruption. We expect you to be passionate about technology, curious about AI, and eager to use both to create tangible impact for our users and partners.
Key Responsibilities:- Design, build, and maintain AI-powered full-stack applications that improve user experience and internal tools.
- Develop and operate scalable backend services & APIs for AI/ML workloads using languages such as Python, Golang, or Node.js.
- Productionize ML / GenAI solutions, including:
- Retrieval-Augmented Generation (RAG) for support, content, and internal tools
- Recommendation and ranking services
- Classification, quality scoring, and enrichment pipelines
- Implement and evolve the AI/ML platform, including:
- Feature and embeddings stores
- Vector search / semantic search infrastructure
- Evaluation dashboards, prompt/version management, and feedback loops
- Own services end-to-end: from design and implementation to monitoring, observability, and on-call, ensuring high availability, performance, and reliability.
- Collaborate with cross-functional teams (Product, Data Science, Data Engineering, Design, DevOps/SRE) to translate business problems into robust technical solutions.
- Apply cloud-native and DevOps best practices, using AWS and containerization (ECS/EKS, Docker, etc.), CI/CD (GitHub Actions, Jenkins, etc.), and infrastructure-as-code.
- Implement security, data protection, and responsible AI guardrails, ensuring safe and compliant use of models and data.
- Participate in code reviews and help define and drive engineering best practices across the team.
- Mentor and support other engineers (and occasionally data scientists), sharing knowledge on software design, clean code, and reliable ML in production.
- Stay up to date with emerging AI/ML and software engineering trends and proactively propose improvements to our stack and ways of working.
Desired Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
- 7+ years of professional experience in software engineering, with significant exposure to backend and distributed systems.
- Strong proficiency with one or more backend languages: Golang, NodeJS, or Python
- Solid understanding of cloud architecture and cloud-native technologies, preferably AWS.
- Experience designing and operating highly distributed, scalable services with strong observability (metrics, logs, traces, dashboards, alerts).
- Familiarity with MLOps practices and tools: CI/CD for ML, model deployment patterns, monitoring model performance and data drift.
- Knowledge of relational and NoSQL databases, including schema design and query optimization.
- Strong understanding of DevOps practices and CI/CD pipelines using tools such as GitHub Actions, Jenkins, and Git.
- Excellent problem-solving skills, attention to detail, and a strong sense of ownership.
- Great communication and teamwork abilities, comfortable collaborating in cross-functional Agile teams.
- Hands-on experience with AI/ML or GenAI in production, such as:
- Fine-tuning or integrating transformer models
- Building RAG pipelines and semantic search
- Working with vector databases (e.g., Pinecone, Weaviate, Milvus, OpenSearch, etc.)
- Self-motivated and proactive, able to work independently where needed while contributing to team outcomes.
- Passion for clean, efficient, maintainable code, and for turning AI/ML ideas into reliable, user-facing products.
- Ability and willingness to mentor junior engineers and contribute to the growth of the team’s AI/ML and software engineering capabilities.