Python Developer/ AI Engineering

Highmark Health • Pittsburgh, PA

15h • Remote

About The Position

Airetel Staffing is seeking a Python Developer / AI Engineer for a valued client. The role focuses on building and supporting AI-enabled backend services, with work spanning Python development, Generative AI and RAG workflows, GCP services, API integration, cloud deployment, and troubleshooting. The position is remote.

The developer will build production-ready Python services and FastAPI endpoints, integrate LLM-based capabilities and retrieval workflows, and process structured and unstructured data. The role also includes testing, debugging, deployment support, documentation, and collaboration with architects, infrastructure teams, product owners, and business stakeholders. The ideal candidate is a mid-level developer who can independently deliver AI-enabled backend components and work with senior engineers on complex design decisions.

Requirements

• 4–7 years of software development experience, including strong hands-on Python backend development.
• At least 1–2 years of practical experience with Generative AI, LLM-based applications, or RAG solutions.
• Experience building REST APIs with FastAPI, Flask, or similar Python frameworks; FastAPI is preferred.
• Hands-on GCP experience, especially with Cloud Run, Cloud Storage, Vertex AI, BigQuery, Pub/Sub, IAM, and Secret Manager.
• Experience integrating AI/ML services into enterprise applications using APIs, authentication, asynchronous processing, and cloud-native services.
• Experience processing structured and unstructured 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 through logs, monitoring, request tracing, and error analysis.
• Experience working in Agile delivery teams and collaborating with cross-functional stakeholders.
• Strong Python programming fundamentals, including object-oriented design, modular coding, exception handling, testing, and package management.
• Generative AI/LLM skills including prompt engineering, structured outputs, model invocation, response validation, token usage, and basic evaluation concepts.
• RAG skills including document ingestion, chunking, embeddings, vector retrieval, metadata filtering, reranking, and grounding.
• Practical GCP skills with Vertex AI, Vertex AI Search, Cloud Run, GCS, BigQuery, Pub/Sub, Secret Manager, IAM, and Cloud Logging.
• FastAPI/REST API skills including endpoint development, request/response models, authentication, asynchronous processing, status handling, and API integration.
• Data-processing skills with pandas, openpyxl, JSON/JSONL handling, document processing, validation, and transformation.
• Cloud-native development experience with Docker, service accounts, environment variables, secrets, CI/CD, deployment, and runtime troubleshooting.
• Git skills including branching, pull requests, merge conflict resolution, version control, and collaborative development.
• Testing and debugging skills including unit, API, and integration testing; Postman or cURL; log analysis; and production issue troubleshooting.

Nice To Haves

• Experience with Agentic AI frameworks or multi-step AI orchestration.
• Familiarity with Vertex AI Vector Search, Graph RAG, or knowledge graph concepts.
• Experience with Pub/Sub-based asynchronous processing and event-driven architectures.
• Understanding of OAuth, service-to-service authentication, IAM, signed URLs, and secure API integration.
• Exposure to React or frontend integration.
• Familiarity with AI evaluation metrics such as groundedness, relevance, completeness, coherence, and confidence scoring.
• Healthcare-domain exposure, particularly involving enterprise workflows, requirements, or document intelligence.

Responsibilities

• Design, develop, and maintain modular, production-ready Python backend services and APIs for AI-enabled applications.
• Build and integrate Generative AI workflows using LLMs, RAG pipelines, prompt orchestration, and structured-output processing.
• Develop FastAPI REST endpoints for file processing, pipeline execution, asynchronous workflows, and integration with enterprise applications.
• Implement retrieval workflows using GCP services, including Vertex AI, Vertex AI Search, Cloud Storage, BigQuery, Pub/Sub, Secret Manager, and Cloud Run.
• Develop data-processing logic for structured and unstructured inputs, including document parsing, metadata generation, validation, transformation, and downstream persistence.
• Support integration testing, debugging, deployment, logging, monitoring, and troubleshooting across development and QA environments.
• Collaborate with solution architects, cloud infrastructure teams, product owners, and business stakeholders to translate requirements into AI features and scalable backend components.
• Contribute to prompt engineering, output validation, error handling, retry logic, and guardrails for reliable AI pipeline responses.
• Maintain technical documentation, API contracts, configuration files, deployment artifacts, and reusable engineering components.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed