Python Developer
Confidential · Pittsburgh, Pennsylvania, United States
FULL TIME
Job Description
Please note: This is a 3 months contract role
Make your application after reading the following skill and qualification requirements for this position.
Job SummaryDevelop 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 ResponsibilitiesDesign, 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 Requirements4–7 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 AbilitiesPython: 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 CharacteristicsAgentic 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 EnvironmentCloud-hosted engineering work in Agile, cross-functional teams. Development and QA environment support is required. xzbcwsv Location, remote/onsite schedule, and travel expectations are not specified.
Make your application after reading the following skill and qualification requirements for this position.
Job SummaryDevelop 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 ResponsibilitiesDesign, 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 Requirements4–7 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 AbilitiesPython: 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 CharacteristicsAgentic 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 EnvironmentCloud-hosted engineering work in Agile, cross-functional teams. Development and QA environment support is required. xzbcwsv Location, remote/onsite schedule, and travel expectations are not specified.
Details
| Company | Confidential |
| Location | Pittsburgh, Pennsylvania, United States |
| Type | FULL TIME |
| Niche | hr |

