Key ResponsibilitiesDevelop and maintain Python-based backend systems to integrate AI/ML models into production environments.Design, build, and manage APIs and connectors for integrating with enterprise systems (e.g., CRMs, ERPs, databases, cloud platforms).Collaborate with AI/ML teams to productionize models and ensure smooth deployment, versioning, and monitoring.Implement and manage data pipelines for real-time and batch data ingestion.Assist in developing automation and orchestration scripts using Python and integration tools.Troubleshoot and resolve issues related to system integrations and AI model performance.Work with DevOps teams to manage deployment pipelines, CI/CD processes, and infrastructure as codeEnsure compliance with data governance, security, and privacy standards during integration.Communicate with clients and internal stakeholders to gather requirements and deliver tailored AI solutions.
Requirements
Technical SkillsStrong proficiency in Python, including experience with libraries like FastAPI, Flask, Pandas, and NumPy.Experience with RESTful APIs, webhooks, and third-party API integration.Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and how to deploy models.Knowledge of cloud platforms (AWS, Azure, GCP) and associated services (e.g., Lambda, S3, Cloud Functions, Pub/Sub).Experience with message brokers and event-driven systems (e.g., Kafka, RabbitMQ).Proficient in Git, Docker, and CI/CD workflows.Understanding of microservices architecture and container orchestration (e.g., Kubernetes).Soft SkillsStrong analytical and problem solving skills.Effective communication skills and ability to explain technical concepts to non-technical stakeholders.Ability to work independently as well as part of a collaborative cross-functional team.Client-focused mindset with the ability to gather requirements and deliver customized solutions.Preferred Qualifications
Experience with low code no-code integration platforms (e.g., Zapier, MuleSoft, Make.com).Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Kubeflow).Previous experience in a client-facing or consulting role.Exposure to data privacy regulations e.g., GDPR, HIPAAMust-Have:
3 plus years experience in Python development, with a focus on backend or data-related systems.Solid understanding of REST APIs, webhooks, OAuth2, and other integration technologies.Experience deploying and integrating AI/ML models into real-world applications.Familiarity with AI ML concepts (NLP, computer vision, classification, etc.) even if not directly building models.Experience with one or more cloud platforms (AWS, GCP, Azure).Experience working with structured and unstructured data formats (JSON, XML, CSV, images, etc.).Must-Have:
3+ years experience in Python development, with a focus on backend or data-related systems.Solid understanding of REST APIs, webhooks, OAuth2, and other integration technologies.Experience deploying and integrating AI/ML models into real-world applications.Familiarity with AI/ML concepts (NLP, computer vision, classification, etc.) even if not directly building models.Experience with one or more cloud platforms (AWS, GCP, Azure).Experience working with structured and unstructured data formats (JSON, XML, CSV, images, etc.).