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Python Developer - AI Engineering​/GenAI

Remote / Online - Candidates ideally in
Ann Arbor, Washtenaw County, Michigan, 48113, USA
Listing for: BlackCube Labs
Remote/Work from Home position
Listed on 2026-10-19
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Python, Backend Developer
Salary/Wage Range or Industry Benchmark: 120000 - 160000 USD Yearly USD 120000.00 160000.00 YEAR
Job Description & How to Apply Below
Python Developer - AI Engineering / GenAI

Tek Wissenis a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. Our client is a health and wellness organizationlocatedin Pittsburgh andoperateshealth insurance plans in Pennsylvania, Delaware, and West Virginia.

Job Title:

Python Developer – AI Engineering / GenAI

Location:
Remote

Duration: 3

Months

Job Type:Temporary Assignment

Work Type:
Remote

Job Description:

  • Design, develop, and maintain Python-based backend services and APIs for AI-enabled applications, with strong emphasis on clean, modular, production-ready code.
  • Build and integrate Generative AI workflows using LLMs, RAG pipelines, prompt orchestration, and structured-output processing.
  • Develop FastAPI-based REST endpoints to support file processing, pipeline execution, asynchronous workflows, and integration with external enterprise applications.
  • Implement retrieval workflows using GCP services such as Vertex AI, Vertex AI Search, Cloud Storage, Big Query, 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 of AI applications across development and QA environments.
  • Collaborate with solution architects, cloud infrastructure teams, product owners, and business stakeholders to translate requirements into working AI features and scalable backend components.
  • Contribute to prompt engineering, output validation, error handling, retry logic, and guardrails to improve reliability of AI pipeline responses.
  • Maintain technical documentation, API contracts, configuration files, deployment artifacts, and reusable engineering components.
Required Experience:
  • 4–7 years of software development experience, with strong hands-on experience in Python backend development.
  • At least 1–2 years of practical experience with Generative AI, LLM-based applications, or RAG solutions.
  • Experience building REST APIs using FastAPI, Flask, or similar Python frameworks, preferably FastAPI.
  • Hands‑on experience working with Google Cloud Platform, especially Cloud Run, Cloud Storage, Vertex AI, Big Query, 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 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, Git Lab/Git Hub, and cloud deployment pipelines.
  • Exposure to debugging distributed or cloud-hosted applications using logs, monitoring, request tracing, and error analysis.
  • Experience working in Agile delivery teams and collaborating with cross-functional stakeholders.
Must-Have Skill Set:
  • Python – strong programming fundamentals, object-oriented design, modular coding, exception handling, testing, and package management.
  • Generative AI / LLMs – prompt engineering, structured outputs, model invocation, response validation, token usage, and basic evaluation concepts.
  • RAG – document ingestion, chunking, embeddings, vector retrieval, metadata filtering, reranking, and grounding.
  • GCP – practical experience with Vertex AI, Vertex AI Search, Cloud Run, GCS, Big Query, Pub/Sub, Secret Manager, IAM, and Cloud Logging.
  • FastAPI / REST APIs – endpoint development, request/response models, authentication, async processing, status handling, and API integration.
  • Data Processing – pandas, openpyxl, JSON/JSONL handling,…
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