Python Developer

Please note: This is a 3 months contract role

Job Summary

Develop and support production-ready Python backend services and APIs for AI-enabled enterprise applications. Build Generative AI and retrieval-augmented generation (RAG) workflows, integrate Google Cloud Platform services, and support testing, deployment, and troubleshooting of scalable AI solutions.

Key Responsibilities

• Design, develop, and maintain modular Python backend services and APIs for AI-enabled applications.
• Build LLM and RAG pipelines, including prompt orchestration, structured output processing, validation, and guardrails.
• Develop REST APIs, preferably with FastAPI, for document processing, pipeline execution, asynchronous operations, and enterprise integrations.
• Implement retrieval and processing workflows using Vertex AI, Vertex AI Search, Cloud Storage, BigQuery, Pub/Sub, Secret Manager, and Cloud Run.
• Process structured and unstructured documents; perform parsing, metadata generation, validation, transformation, and persistence.
• Support integration testing, debugging, deployment, logging, monitoring, and troubleshooting in development and QA environments.
• Collaborate with architects, infrastructure teams, product owners, and stakeholders to deliver scalable AI functionality.
• Maintain API contracts, documentation, configuration, deployment artifacts, and reusable components.

Minimum Education & Experience Requirements

• 4–7 years of software development experience with strong hands-on Python backend development.
• At least 1–2 years of practical experience building Generative AI, LLM-based, or RAG applications.
• Experience building REST APIs with FastAPI, Flask, or a similar Python framework.
• Hands-on GCP experience, including Cloud Run, Cloud Storage, Vertex AI, BigQuery, Pub/Sub, IAM, and Secret Manager.
• Experience integrating AI/ML services into enterprise applications with APIs, authentication, asynchronous processing, and cloud-native services.
• Experience with structured and unstructured formats, Git, Docker, CI/CD, cloud deployment, debugging, and Agile collaboration.
• No specific degree requirement stated.

Knowledge, Skills, and Abilities

• Python: OOP, modular coding, exception handling, unit testing, and package management.
• GenAI: prompts, model invocation, structured outputs, token usage, response validation, and basic evaluation.
• RAG: ingestion, chunking, embeddings, vector retrieval, metadata filtering, reranking, and grounding.
• GCP: Vertex AI, Vertex AI Search, Cloud Run, GCS, BigQuery, Pub/Sub, IAM, Secret Manager, and Cloud Logging.
• FastAPI/REST: endpoint design, request/response models, authentication, asynchronous processing, and integration.
• Data processing: pandas, openpyxl, JSON/JSONL, Excel, CSV, PDF, Word, and text.
• Git, Docker, service accounts, secrets, CI/CD, Postman/cURL, logging, and troubleshooting.

Additional Desired Characteristics

• Agentic AI frameworks or multi-step orchestration.
• Vertex AI Vector Search, Graph RAG, or knowledge graphs.
• Pub/Sub event-driven architectures; OAuth, signed URLs, and secure service-to-service authentication.
• React or frontend integration exposure.
• AI evaluation metrics including groundedness, relevance, completeness, coherence, and confidence scoring.
• Healthcare-domain exposure, especially enterprise workflows or document intelligence.
• FastAPI experience is preferred over other qualifying Python API frameworks.

Work Environment

Cloud-hosted engineering work in Agile, cross-functional teams. Development and QA environment support is required. Location, remote/onsite schedule, and travel expectations are not specified.