Software Gigs

Sr. Director role overseeing SIE's data and AI platform ecosystem, including data infrastructure (streaming, ingestion, warehouse), experimentation platforms, and governance tools. Responsible for defining long-term vision, leading global engineering teams, and ensuring platforms process massive data volumes to deliver insights across gaming, content creation, and enterprise operations. Must drive scalability, cost efficiency, security, and operational excellence while collaborating with senior leadership to align platform strategy with business objectives. Requires proven Sr. Director-level experience and thought leadership in platform architecture, real-time data processing, and ML/AI integration.

Own and deliver small to medium machine learning system components from design through production deployment, including building data pipelines, training and evaluating models, and implementing MLOps monitoring. Write high-quality Python code to translate technical requirements into maintainable solutions, working with frameworks like scikit-learn, TensorFlow, PyTorch, and HuggingFace. Design and deploy ML models as microservices, APIs, batch jobs, or streaming components on AWS, with responsibility for model performance metrics, data drift detection, and retraining triggers. Collaborate across Data Engineers, Software Engineers, Data Scientists, and product stakeholders to deliver project objectives.

The MMIS Developer – Supply Chain designs and develops supply chain software systems, translating business requirements into technical solutions. Responsibilities include leading development projects, maintaining critical analytics and databases, troubleshooting system issues, and creating reports. The role requires proficiency with VBA, SQL Server, and business intelligence tools like Power BI, with preferred experience in Lawson, Epic, Python, and Snowflake for supply chain analytics.

The Data Architect is a hands-on technical leader responsible for designing and modernizing enterprise data architecture across on-premises and cloud platforms. The role defines scalable data models, integration patterns, and architectural standards for the Data Lake, Data Warehouse, ODS, and cloud platforms while ensuring security, resilience, and high performance. Working closely with engineering, analytics, and business teams, the architect provides technical guidance on modern data systems, governance frameworks, and ETL/ELT pipelines. The position combines strategic vision with practical experience optimizing structured, semi-structured, and unstructured workloads across SQL, NoSQL, and cloud-native systems.

Ignite Digital seeks an AI Engineer to own the end-to-end machine learning lifecycle—from data preparation and model training through production deployment and monitoring. You will integrate AI models into frontend and backend systems, optimize performance for latency and cost, and collaborate with technical leads and customers to deliver Data and AI solutions. The role requires strong Python and cloud platform expertise (AWS, Azure, or GCP), software engineering fundamentals, and the ability to communicate technical opportunities and limitations across varying levels of technical experience.

The Data Architect is a hands-on technical leader responsible for designing and modernizing enterprise data architecture across on-premises and cloud platforms. The role defines scalable data models, cloud-native integration patterns, and architectural standards supporting analytics, reporting, and digital banking applications. This position combines strategic architectural vision with practical expertise in designing, implementing, and optimizing modern data systems across structured, semi-structured, and unstructured workloads. The architect provides technical leadership to Data Engineers and cross-functional teams while ensuring secure, resilient, and high-performing data environments.

The Applied AI Engineer develops, deploys, and maintains generative AI solutions for insurance products and internal workflows. The role involves implementing end-to-end AI pipelines using AWS services (SageMaker, Lambda, ECS/EKS, S3), building feature engineering workflows in Snowflake, and collaborating with cloud and MLOps teams. Candidates need 3+ years of AI/ML engineering experience with 1–2 years focused on generative AI or LLMs, proficiency in Python and frameworks like PyTorch or Hugging Face Transformers, and hands-on cloud deployment experience. The position requires monitoring model performance, ensuring security and compliance, and supporting AI architecture reviews.

Design, build, and scale ETL/ELT pipelines and cloud data warehouse infrastructure using Python, SQL, and modern orchestration tools like Apache Airflow or Prefect. Own the end-to-end data infrastructure that powers business intelligence and operational reporting, including data quality checks, anomaly detection, and performance optimization. Collaborate with analytics and software engineering teams to define data modeling standards and maintain infrastructure-as-code deployments using Terraform and CI/CD. Requires 3–6 years of data engineering or backend development experience with advanced SQL, Python, and hands-on work with cloud data warehouses like Snowflake or BigQuery.

Senior Applied AI Engineer at West Health will design, build, and deploy production-quality AI-powered tools and workflows using large language models, multi-agent architectures, and orchestration platforms. The role involves building intelligent automation pipelines with tools like n8n, LangChain/LangGraph, and Microsoft Copilot Studio, integrating AI capabilities with existing data infrastructure (Snowflake, Python), and conducting data analysis to identify high-impact AI opportunities. The ideal candidate combines deep practical expertise in applied AI with the ability to rapidly move from concept to fully working, well-documented applications that create measurable value for healthcare delivery and senior care initiatives.

Senior Database Engineer II will build and maintain scalable data pipelines using Azure Data Factory, Databricks, Azure Synapse Analytics, and Snowflake. The role requires designing and implementing conceptual, logical, and physical data models, leading system integration efforts, and architecting multi-tenant database solutions for the medical device industry. You'll provide technical leadership on data engineering standards, conduct code and design reviews, and collaborate across geographically dispersed teams in an Agile environment. The position demands 7+ years of database design and software development experience, with a strong focus on healthcare compliance and data governance.