Software Engineer

Location: Addison, TX
Salary: $69.00 USD Hourly - $74.00 USD Hourly
Description:
Role: Senior Software Engineer (Contingent Resource)
Location: Addison, TX

As a Senior Software Engineer in this contingent role, you will contribute to high-impact, large-scale software engineering initiatives. You'll work on complex technical challenges, collaborate with cross-functional teams, and help shape scalable, secure, and efficient systems across multi-cloud environments.
Responsibilities:

• Lead and consult on large-scale software engineering projects with broad technical scope and strategic impact.
• Analyze and solve complex, multi-dimensional engineering problems involving novel or ambiguous factors.
• Design and implement hybrid cloud solutions across AWS, Google Cloud Platform, and Azure, ensuring high availability, scalability, and cost optimization.
• Build and maintain RESTful APIs using FastAPI and Swagger for real-time LLM inference and scalable model serving pipelines.
• Optimize generative AI models (e.g., LLaMA, Mistral, OpenAI GPT) and implement Retrieval-Augmented Generation (RAG) pipelines using Ray and VectorAI.
• Automate infrastructure provisioning and management using Terraform, Ansible, and Crossplane for multi-cloud deployments.
• Support reproducible and scalable ML pipelines using tools like MLflow, DVC, and VectorAI.
• Provision GPU-accelerated infrastructure to enhance LLM training performance by up to 50%.
• Integrate Apache Iceberg with vector databases (e.g., Milvus, Pinecone) for semantic search and dataset lineage tracking.
• Orchestrate real-time and batch data workflows using Apache Airflow, Spark, and Flink.
• Implement observability solutions using Prometheus, Datadog, and Splunk to monitor system health and performance.
• Design dashboards and metrics pipelines to deliver actionable insights and reduce debugging time.

Minimum Qualifications:

• 5+ years of experience in software engineering or equivalent experience through work, consulting, military service, or education.
• Proven expertise in multi-cloud architecture and infrastructure automation.
• Strong background in building scalable AI/ML systems and APIs.
• Experience with distributed systems, data engineering, and observability tools.

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