Python Developer – AI Engineering / GenAI (REMOTE)
- Source: LinkedIn
- RadGov Inc.
- Remote
- Pittsburgh
- Mid level
Job Description
Job Title: Python Developer – AI Engineering / GenAI (REMOTE)
Duration: 04+Months
Pay rate: $75.00-$78.00/hr on W2 .
Location: REMOTE
Glider assessment : AI Engineer
100% REMOTE
Roles & Responsibilities:
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Design, develop, and maintain Python-based backend services and APIs for AI-enabled applications, with strong emphasis on clean, modular, production-ready code.
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Build and integrate Generative AI workflows using LLMs, RAG pipelines, prompt orchestration, and structured-output processing.
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Develop FastAPI-based REST endpoints to support file processing, pipeline execution, asynchronous workflows, and integration with external enterprise applications.
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Implement retrieval workflows using GCP services such as Vertex AI, Vertex AI Search, Cloud Storage, BigQuery, Pub/Sub, Secret Manager, and Cloud Run.
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Develop data-processing logic for structured and unstructured inputs, including document parsing, metadata generation, validation, transformation, and downstream persistence.
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Support integration testing, debugging, deployment, logging, monitoring, and troubleshooting of AI applications across development and QA environments.
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Collaborate with solution architects, cloud infrastructure teams, product owners, and business stakeholders to translate requirements into working AI features and scalable backend components.
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Contribute to prompt engineering, output validation, error handling, retry logic, and guardrails to improve reliability of AI pipeline responses.
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Maintain technical documentation, API contracts, configuration files, deployment artifacts, and reusable engineering components.
Required Experience:
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4–7 years of software development experience, with strong hands-on experience in Python backend development.
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At least 1–2 years of practical experience with Generative AI, LLM-based applications, or RAG solutions.
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Experience building REST APIs using FastAPI, Flask, or similar Python frameworks, preferably FastAPI.
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Hands-on experience working with Google Cloud Platform, especially Cloud Run, Cloud Storage, Vertex AI, BigQuery, Pub/Sub, IAM, and Secret Manager.
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Experience integrating AI/ML services into enterprise applications using APIs, authentication, asynchronous processing, and cloud-native services.
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Experience processing structured and unstructured data formats such as JSON, JSONL, Excel, CSV, PDF, Word documents, and text.
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Experience with source control, CI/CD, containerization, and deployment workflows using Git, Docker, GitLab/GitHub, and cloud deployment pipelines.
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Exposure to debugging distributed or cloud-hosted applications using logs, monitoring, request tracing, and error analysis.
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Experience working in Agile delivery teams and collaborating with cross-functional stakeholders.
Must-Have Skill Set:
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Python – strong programming fundamentals, object-oriented design, modular coding, exception handling, testing, and package management.
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Generative AI / LLMs – prompt engineering, structured outputs, model invocation, response validation, token usage, and basic evaluation concepts.
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RAG – document ingestion, chunking, embeddings, vector retrieval, metadata filtering, reranking, and grounding.
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GCP – practical experience with Vertex AI, Vertex AI Search, Cloud Run, GCS, BigQuery, Pub/Sub, Secret Manager, IAM, and Cloud Logging.
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FastAPI / REST APIs – endpoint development, request/response models, authentication, async processing, status handling, and API integration.
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Data Processing – pandas, openpyxl, JSON/JSONL handling, document processing, validation, and transformation.
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Cloud-Native Development – Docker, service accounts, environment variables, secrets, CI/CD, deployment, and runtime troubleshooting.
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Git – branching, pull requests, merge conflict resolution, version control, and collaborative development.
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Testing & Debugging – unit testing, API testing, integration testing, Postman/cURL, log analysis, and production issue troubleshooting.
Preferred / Good-to-Have Skills:
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Experience with Agentic AI frameworks or multi-step AI orchestration.
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Familiarity with Vertex AI Vector Search, Graph RAG, or knowledge graph concepts.
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Experience with Pub/Sub-based asynchronous processing and event-driven architectures.
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Understanding of OAuth, service-to-service authentication, IAM, signed URLs, and secure API integration.
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Exposure to React or frontend integration …
Skills
- Python
- glide-2
- FastAPI
- google-cloud-platform
- vertex
- guardrails
- Flask
- google-cloud-run
- google-cloud-storage
- google-bigquery
- JSON
- Docker
- gitlab
- Github
- processing-js
- Pandas
- postman
- curl
- microsoft-graph
- oauth
- React
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