AI Applications Developer

DescriptionAbout the RoleWe 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.Key Responsibilities 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.RequirementsRequired Qualifications 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 DevOps 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.Preferred Qualifications Experience with frontend technologies (React/TypeScript) 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.Skills and Technologies (Examples) Languages: Python, JavaScript/TypeScript (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, NumPy, data pipelines, ETL Cloud & DevOps: AWS/Azure/GCP, Docker, Kubernetes, CI/CD (GitHub Actions, GitLab CI) Databases: PostgreSQL, MongoDB, Redis AI/ML Tools: OpenAI API, Pinecone/Weaviate, MLflow, PyTorch/TensorFlow (nice-to-have) Observability: Prometheus, Grafana, ELK/EFK stackNice-to-Have 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 HIPPA data privacy impact assessments and security reviewsWhat We Offer 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 resourcesHow To ApplyPlease submit: Your resume/CV A brief cover letter outlining relevant AI app projects Links to a portfolio, GitHub, or live projects if available