AI Applications Developer

About the Role

We are seeking a motivated AI Applications Developer to design, build, and deploy AI-powered software that delivers tangible value to users. You will work across product, data science, and frontend/backend engineering to turn ideas into scalable, production‑ready AI features and apps. You’ll own the full lifecycle from concept and architecture to implementation, testing, and operations, with a focus on reliability, performance, and ethical AI practices.

• Design and implement AI-powered features and applications, including chatbots, assistants, search/retrieval, summarization, recommendations, vision-based features, or other ML-driven capabilities.
• Build robust backend services and APIs to expose AI functionality; ensure low latency, high throughput, and scalable architecture.
• Integrate AI models and pipelines with frontend products; collaborate with UI/UX to deliver intuitive AI-enhanced experiences.
• Develop and maintain data pipelines, feature stores, and data preprocessing steps; ensure data quality, privacy, and security.
• Evaluate models for performance, fairness, bias, latency, and reliability; implement monitoring, A/B testing, and rollback strategies.
• Implement MLOps practices: versioning, CI/CD for ML, containerization (e.g., Docker), orchestration (e.g., Kubernetes), and automated testing.
• Monitor applications post-release; instrument logging, metrics, tracing, and alerting; manage incident response and reliability targets.
• Write clean, well‑documented code; create and maintain API docs, architecture diagrams, and developer guides.
• Collaborate with Product, Design, Data Science, and Security teams to translate requirements into concrete technical plans.
• Ensure compliance with privacy, security, and ethical guidelines; implement bias mitigation and explainability where appropriate.
• Contribute to code reviews, unit/integration tests, and continuous improvement of development processes.

• 2+ years of software development experience, with hands‑on work on AI‑enabled or data‑driven applications.
• Proficiency in Python for backend and ML integration; experience with building or consuming AI/ML models and APIs.
• Strong backend development skills and experience with at least one modern framework (e.g., FastAPI, Django, Flask, Node.js/Express).
• Experience integrating AI services or LLMs (e.g., OpenAI, Cohere, Anthropic) and working with embeddings, vector databases (e.g., Pinecone, Weaviate), or retrieval‑based architectures.
• Familiarity with cloud platforms (AWS, GCP, Azure) and basic Dev Ops practices (CI/CD, Docker); basic containerization and orchestration knowledge.
• Knowledge of data privacy, security best practices, and ethical considerations in AI.
• Ability to work cross‑functionally with product managers, designers, and data scientists; strong communication and collaboration skills.
• A track record of writing tests (unit/integration), documentation, and maintaining code quality.

• Experience with frontend technologies (React/Type Script) and integrating AI features into user interfaces.
• Experience with ML pipelines and MLOps tools (MLflow, Kubeflow, Airflow) and monitoring tools (Prometheus, Grafana).
• Familiarity with vector databases, structured/unstructured data processing, and data governance.
• Degree in Computer Science, Engineering, or a related field; advanced degree a plus.
• Knowledge of modern security practices, data anonymization, and GDPR/CCPA compliance.

• Languages:
  
  Python, JavaScript/Type Script (Node.js/React), SQL
• AI/ML: LLMs, embeddings, retrieval, fine‑tuning, evaluation metrics
• Backend:
  FastAPI/Django/Flask, REST/gRPC, microservices
• Frontend:
  React, Next.js (nice‑to‑have)
• Data:
  Pandas, Num Py, data pipelines, ETL
• Cloud & Dev Ops: AWS/Azure/GCP, Docker, Kubernetes, CI/CD (Git Hub Actions, Git Lab CI)
• Databases:
  Postgre
  
  SQL, Mongo
  
  DB, Redis
• AI/ML Tools:
  OpenAI API, Pinecone/Weaviate, MLflow, PyTorch/Tensor Flow (nice‑to‑have)
• Observability:
  Prometheus, Grafana, ELK/EFK stack

• Mendix and JAVA experience
• Production experience with AI‑powered consumer or enterprise applications
• Contributions to open‑source AI projects or prior startup experience
• Experience with privacy‑preserving AI and bias mitigation techniques
• Experience with HIPAA data privacy impact assessments and security reviews

• Competitive compensation and meaningful equity
• Comprehensive health, dental, and vision coverage
• Professional development and opportunities for growth
• Collaborative, inclusive team culture and mentorship
• Modern tech stack and access to AI/ML resources