Python Developer – AI Engineering, GenAI

Job not on LinkedIn

🔥 0 minutes ago

🔔 Pennsylvania – Remote

🔔 Pennsylvania – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Sigma Systems

WebsiteLinkedInAll Job Openings

201 - 500 employees

📡 Telecommunications

⚡ Energy

☁️ SaaS

💰 $11M Venture Round - Tribold on 2009-01

Telecommunications • Energy • SaaS

Sigma Systems is a software company that provides cloud-native, API-driven BSS/OSS, product catalog, CPQ and order orchestration solutions for communications service providers and energy/utilities companies. It offers modular, TMF-compliant components and managed services — including AI-enabled automation and data-driven tools — to help operators modernize billing, monetization, and customer fulfillment processes with a SaaS and cloud-focused delivery model.

📋 Description

• Design, develop, and maintain Python-based 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-based REST endpoints for file processing, pipeline execution, asynchronous workflows, and enterprise application integration • Implement retrieval workflows using GCP services including Vertex AI, Vertex AI Search, Cloud Storage, BigQuery, Pub/Sub, Secret Manager, and Cloud Run • Develop 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 AI features and scalable backend components • Contribute to prompt engineering, output validation, error handling, retry logic, and guardrails to improve AI pipeline reliability • Maintain technical documentation, API contracts, configuration files, deployment artifacts, and reusable engineering components

🎯 Requirements

• 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 with Google Cloud Platform, especially 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 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, GitLab/GitHub, 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 • Strong Python programming fundamentals, object-oriented design, modular coding, exception handling, testing, and package management • Generative AI/LLM knowledge including prompt engineering, structured outputs, model invocation, response validation, token usage, and basic evaluation concepts • RAG knowledge including document ingestion, chunking, embeddings, vector retrieval, metadata filtering, reranking, and grounding • Practical GCP experience 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 skills including 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 testing, API testing, integration testing, Postman/cURL, log analysis, and production issue troubleshooting

🏖️ Benefits

• 4-month contract assignment