Python Developer – AI Engineering, GenAI

This is a fully remote position, open to applicants in Pennsylvania.

📋 Description

• Design, develop, and maintain backend services and APIs using Python for AI-driven applications.

• Create and integrate Generative AI workflows utilizing LLMs, RAG pipelines, prompt orchestration, and structured-output processing.

• Develop REST endpoints based on FastAPI for file processing, pipeline execution, asynchronous workflows, and enterprise application integration.

• Implement retrieval workflows leveraging GCP services such as Vertex AI, Vertex AI Search, Cloud Storage, BigQuery, Pub/Sub, Secret Manager, and Cloud Run.

• Create processing logic for both structured and unstructured inputs, encompassing document parsing, metadata generation, validation, transformation, and downstream persistence.

• Assist with integration testing, debugging, deployment, logging, monitoring, and troubleshooting of AI applications across development and QA environments.

• Collaborate with solution architects, cloud infrastructure teams, product owners, and business stakeholders to convert requirements into AI capabilities and scalable backend components.

• Contribute to prompt engineering, output validation, error handling, retry logic, and guardrails to enhance the reliability of AI pipelines.

• Maintain technical documentation, API contracts, configuration files, deployment artifacts, and reusable engineering components.

⛳️ Requirements

• 4–7 years of experience in software development, with a strong focus on Python backend development.

• At least 1–2 years of hands-on experience with Generative AI, LLM-based applications, or RAG solutions.

• Experience in building REST APIs using FastAPI, Flask, or similar Python frameworks, with a preference for FastAPI.

• Practical experience with Google Cloud Platform, particularly Cloud Run, Cloud Storage, Vertex AI, BigQuery, Pub/Sub, IAM, and Secret Manager.

• Experience in integrating AI/ML services into enterprise applications via APIs, authentication, asynchronous processing, and cloud-native services.

• Familiarity with processing structured and unstructured data formats such as JSON, JSONL, Excel, CSV, PDF, Word documents, and text.

• Experience with source control, CI/CD, containerization, and deployment workflows using Git, Docker, GitLab/GitHub, and cloud deployment pipelines.

• Exposure to debugging distributed or cloud-hosted applications by utilizing logs, monitoring, request tracing, and error analysis.

• Experience working within Agile delivery teams and collaborating with cross-functional stakeholders.

• Strong foundational skills in Python programming, object-oriented design, modular coding, exception handling, testing, and package management.

• Knowledge of Generative AI/LLM concepts including prompt engineering, structured outputs, model invocation, response validation, token usage, and basic evaluation principles.

• Understanding of RAG concepts such as document ingestion, chunking, embeddings, vector retrieval, metadata filtering, reranking, and grounding.

• Practical experience with GCP services including Vertex AI, Vertex AI Search, Cloud Run, GCS, BigQuery, Pub/Sub, Secret Manager, IAM, and Cloud Logging.

• Skills in FastAPI/REST API development, including endpoint creation, request/response models, authentication, asynchronous processing, status handling, and API integration.

• Data processing skills with tools like pandas, openpyxl, JSON/JSONL handling, document processing, validation, and transformation.

• Proficiency in cloud-native development, including Docker, service accounts, environment variables, secrets, CI/CD, deployment, and runtime troubleshooting.

• Git proficiency, including branching, pull requests, merge conflict resolution, version control, and collaborative development.

• Skills in testing and debugging, including unit testing, API testing, integration testing, Postman/cURL, log analysis, and troubleshooting in production environments.

🏝️ Benefits

• 4-month contract assignment.