22039-1 – Remote Python Developer – AI Engineering / GenAI (4 Months) Job Title: Python Developer – AI Engineering / Generative AI (GenAI) Location: Remote Duration: 4 Months Job Type: Contract About Sigma, Inc. (Staffing Agency) Sigma, Inc. is a trusted staffing agency specializing in connecting skilled technology professionals with leading organizations. We partner with clients to deliver talent across software engineering, cloud computing, artificial intelligence, and enterprise technology solutions. As a staffing agency, we offer exciting contract opportunities for professionals looking to contribute to innovative projects and advance their technical expertise. Position Overview: Python Developer – AI Engineering / GenAI Sigma, Inc. is currently recruiting for a Remote Python Developer – AI Engineering / GenAI for one of our clients. This 4-month contract position is an excellent opportunity for a mid-level software developer with hands-on experience in Python backend development, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Google Cloud Platform (GCP). The ideal candidate will develop and maintain AI-powered backend services, build GenAI workflows, integrate cloud-based AI solutions, and support the deployment of scalable, reliable applications. This role requires a strong combination of Python programming, AI application development, API integration, cloud engineering, and troubleshooting skills. Key Responsibilities1. Python Backend Development

• Design, develop, and maintain Python-based backend services and APIs for AI-enabled applications.
• Write clean, modular, reusable, and production-ready code using sound software engineering practices.
• Develop REST APIs using FastAPI or similar Python frameworks to support file processing, AI pipeline execution, and integration with enterprise applications.
• Implement asynchronous processing, request validation, error handling, and exception management.

2. Generative AI and RAG Development

• Build and integrate Generative AI workflows using LLMs, prompt engineering, and structured-output processing.
• Develop Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, text chunking, embeddings, vector retrieval, metadata filtering, and response grounding.
• Implement prompt orchestration, response validation, retry mechanisms, and guardrails to improve AI application reliability.
• Support AI output evaluation and troubleshooting to improve response relevance, accuracy, and completeness.

3. Google Cloud Platform (GCP) and Cloud Integration

• Develop and deploy AI-enabled applications using GCP services, including Vertex AI, Vertex AI Search, Cloud Run, Cloud Storage, BigQuery, Pub/Sub, Secret Manager, and IAM.
• Integrate AI and machine learning services into enterprise applications using secure APIs and cloud-native components.
• Support cloud deployments, configuration management, service accounts, environment variables, and secrets management.
• Work with cloud infrastructure teams to troubleshoot application issues and support reliable deployments.

4. Data Processing and Document Intelligence

• Develop data-processing workflows for structured and unstructured data, including JSON, JSONL, Excel, CSV, PDF, Word documents, and text files.
• Implement document parsing, metadata generation, data validation, transformation, and downstream data persistence.
• Use Python libraries such as pandas and openpyxl to process and validate data.
• Support document-based AI workflows and ensure data is prepared appropriately for retrieval and AI processing.

5. Testing, Deployment, and Troubleshooting

• Perform unit testing, API testing, and integration testing across development and QA environments.
• Debug and resolve issues related to APIs, AI workflows, cloud services, and data-processing pipelines.
• Use application logs, monitoring tools, request tracing, Postman, and cURL to identify and resolve technical issues.
• Support CI/CD pipelines, containerization, and application deployment using Git, Docker, GitHub/GitLab, and cloud deployment tools.

6. Collaboration and Documentation

• Collaborate with solution architects, cloud infrastructure teams, product owners, and business stakeholders to translate requirements into working AI solutions.
• Maintain technical documentation, API contracts, configuration files, deployment artifacts, and reusable software components.
• Participate in Agile development activities, code reviews, and collaborative engineering practices.
• Contribute to continuous improvement of AI workflows, application performance, code quality, and engineering standards.

QualificationsEducation

• A degree in Computer Science, Information Technology, Software Engineering, or a related technical field is beneficial.

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 developing Generative AI applications, LLM-based solutions, or RAG pipelines.
• Experience developing REST APIs using FastAPI, Flask, or similar Python frameworks; FastAPI experience is preferred.
• Hands-on experience with Google Cloud Platform, particularly Vertex AI, Vertex AI Search, Cloud Run, Cloud Storage, BigQuery, Pub/Sub, IAM, and Secret Manager.
• Experience integrating AI/ML services with enterprise applications through APIs, authentication, and asynchronous processing.
• Experience working with structured and unstructured data formats and document-processing workflows.
• Familiarity with Git, Docker, CI/CD pipelines, and cloud application deployment.
• Experience troubleshooting cloud-hosted or distributed applications using logs, monitoring, and error analysis.
• Experience working in Agile teams and collaborating with cross-functional stakeholders.

Must-Have Technical Skills

• Python Development: Strong programming fundamentals, object-oriented design, modular coding, exception handling, testing, and package management.
• Generative AI / LLMs: Prompt engineering, model invocation, structured outputs, response validation, token usage, and basic AI evaluation concepts.
• RAG Pipelines: Document ingestion, chunking, embeddings, vector retrieval, metadata filtering, reranking, and grounding.
• Google Cloud Platform: Practical experience with Vertex AI, Vertex AI Search, Cloud Run, Google Cloud Storage (GCS), BigQuery, Pub/Sub, Secret Manager, IAM, and Cloud Logging.
• FastAPI / REST APIs: API endpoint development, request and response models, authentication, asynchronous processing, status handling, and API integration.
• Data Processing: pandas, openpyxl, JSON/JSONL handling, document processing, data validation, and transformation.
• Cloud-Native Development: Docker, service accounts, environment variables, secrets management, CI/CD, deployment, and runtime troubleshooting.
• Git and Version Control: Branching, pull requests, merge conflict resolution, and collaborative development.
• Testing and Debugging: Unit testing, API testing, integration testing, Postman/cURL, log analysis, and application issue resolution.

Preferred / Good-to-Have Skills

• 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 experience, particularly with enterprise workflows, requirements, or document intelligence solutions.

Ideal Candidate Profile The ideal candidate is a mid-level Python developer with practical Generative AI and GCP experience who can independently build and support AI-enabled backend services. This is primarily a hands-on software engineering role, not a pure data science or traditional backend development position. The candidate should be comfortable working across Python development, LLMs, RAG workflows, FastAPI, GCP services, API integration, cloud deployment, and troubleshooting. Candidates should demonstrate experience building or supporting real-world AI applications rather than having only theoretical knowledge of AI or completing introductory AI courses. Why Work with Sigma, Inc.?

• Access to exciting contract opportunities with leading organizations.
• Opportunities to work on innovative Generative AI and cloud engineering projects.
• Exposure to modern AI technologies, enterprise application integration, and Google Cloud services.
• Support from Sigma, Inc. throughout the recruitment and assignment process.

How to Apply

If you have strong Python development skills and hands-on experience with Generative AI, RAG pipelines, and Google Cloud Platform, we encourage you to apply. Please submit your updated resume highlighting your relevant Python, GenAI/LLM, RAG, FastAPI, and GCP project experience. Sigma, Inc. is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. Remote Skills: API Documentation, Adobe Acrobat, Agile Programming Methodologies, Application Programming Interface (API), Artificial Intelligence (AI), Artificial Intelligence (AI) Programming Languages, Audio Engineering, Authentication, Cloud Applications, Cloud Architecture, Cloud Computing, Cloud Storage, Code Reviews, Computer Programming, Computer Science, Configuration Management, Conflict Resolution, Continuous Deployment/Delivery, Continuous Improvement, Continuous Integration, Cross-Functional, Data Processing, Data Quality, Data Science, Debugging Skills, Diversity, Docker, Document Data Formats, Engineering, Enterprise Application Integration (EAI), Error Handling, GCP (Good Clinical Practices), Git, GitHub, Graph Search, Healthcare, Identify Issues, Information Technology Software, Integration Testing, JSON, Mail Services, Metadata, Metrics, Microsoft Excel, Microsoft Word, Modeling Languages, OAuth, Object Oriented Design (OOD), Object Oriented Programming (OOP), Problem Solving Skills, Python Programming/Scripting Language, Quality Assurance, Quality Engineering, REST (Representational State Transfer), Recruiting/Staffing Agency, Reliability Engineering, Requirements Management, Software Development, Software Engineering, Source Code/Configuration Management (SCM), Structured Data, Support Documentation, Team Player, Technical Writing, Test Plan/Schedule, Testing, Unit Test, Unstructured Data, User Interface/Experience (UI/UX) Sigma Inc