Software Gigs

As a Sr. Staff Software Engineer on Qualcomm's AI Software team, you will design and develop the Qualcomm AI Runtime (QAIRT) SDK for IoT platforms, enabling efficient execution of deep neural networks, LLMs, and modern AI architectures. You will lead feature development, mentor junior engineers, and collaborate across cross-functional teams to deliver scalable AI software solutions. The role requires 8+ years of software development experience with strong C/C++ and Linux proficiency, hands-on technical leadership, and the ability to keep pace with rapid industry and academic advances in machine learning and software engineering.

Senior Software Engineer/Research Scientist applying advanced mathematical and algorithmic expertise to defense technology development. Responsibilities include algorithm development in probability, statistics, estimation theory, machine learning, and optimization; designing and maintaining C++ software applications in Linux environments; prototyping AI/ML solutions in MATLAB, Python, and TensorFlow; and managing DevOps workflows using GitLab, Docker, and Podman. Requires 10+ years of engineering experience, a B.S. in engineering/mathematics, and ability to obtain a DoD Secret clearance.

Design and implement software integrations connecting lab automation infrastructure (liquid handlers, plate readers, robotic workstations, analytical instruments) with orchestration layers and digital workflows. Build production-grade Python applications and containerized services using Docker and Kubernetes, deploy CI/CD pipelines, and maintain LIMS integrations. Explore AI-driven decision-making and autonomous orchestration capabilities, staying current with LLM tooling and agent frameworks. Provide technical leadership and mentorship to the automation engineering team while shaping the roadmap for closed-loop autonomous discovery systems.

As an AI Software Engineer at Qualcomm, you will develop and optimize machine learning software for the Qualcomm AI Stack (QAIRT and Genie SDKs), enabling efficient execution of large language models and deep neural networks on Snapdragon platforms. You will validate and optimize performance of generative AI models, debug complex issues, and collaborate across teams to deliver robust AI solutions. The role requires strong software design, programming, and debugging skills, with expertise in machine learning frameworks, embedded systems optimization, and languages like Python or C++. You will work with minimal supervision, participate in design reviews, and contribute to a culture of technical excellence.

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.

Design and develop advanced Power BI dashboards using DAX, Power Query, and complex data modeling techniques. Consolidate and transform data from APIs, files, and SQL databases into reliable reporting models using ETL workflows with SSIS and T-SQL. Build scalable reporting solutions and partner with business users to translate requirements into technical implementations in a fast-paced, multi-project environment. Requires 3+ years of hands-on experience with DAX, Power Query, T-SQL, SSIS, and strong SQL development skills including stored procedures and query optimization.

Lead end-to-end development of AI agents and autonomous engineering tools for Teradata's enterprise platform, managing multiple global engineering teams. Shape engineering strategy for agent platforms, LLM gateways, vector stores, observability frameworks, and low-code/no-code/pro-code agent frameworks. Drive architecture standardization, governance practices, operationalization pipelines, and ROI metrics while partnering with product, architecture, and AI platform teams. Requires 12+ years software engineering experience with 5+ years in technical leadership, hands-on expertise with LLMs, agent frameworks, distributed systems, cloud platforms (AWS, Azure, GCP), and modern CI/CD tools.

Design, build, and maintain enterprise data pipelines using Microsoft Fabric and Azure Synapse, handling ingestion, transformation, and orchestration from ERP and supply chain systems. Develop and manage Fabric Lakehouse and Warehouse architectures, apply data modeling best practices, and ensure data quality and reliability. Collaborate with analytics, BI, and IT teams to create governed, scalable analytical data assets that support Power BI and downstream consumers. Requires a bachelor's degree in a quantitative field, strong SQL and Python skills, and hands-on experience with Microsoft Fabric and Azure Synapse.

Lead the entire engineering team at a VC-backed AI trading firm, combining hands-on ML research and model development with technical leadership. Own the end-to-end development of production AI systems deployed in live financial markets, including model design, training, evaluation, and infrastructure. Set technical direction across ML and software engineers, drive hiring and team development, and translate research into measurable real-world trading performance. Require 5–8 years of applied ML/AI experience with 3+ years managing full engineering teams.

Data Engineer II will maintain and enhance data infrastructure, pipelines, and models supporting manufacturing analytics and operational reporting at Dexcom. The role involves writing and optimizing SQL queries, supporting ETL/ELT pipeline development in BigQuery using tools like Google Cloud Dataflow, Apache Beam, and dbt, and troubleshooting data quality issues. You will partner with business stakeholders to gather requirements, document data lineage and workflows, and develop foundational GCP cloud engineering skills. The ideal candidate has a technical degree or equivalent experience and enjoys solving practical operational problems while learning modern cloud data practices.

Design, develop, and deploy end-to-end generative AI solutions including GenAI agents, LLMs, and applications to solve complex business challenges. Build data pipelines, design APIs for AI accessibility, and collaborate with cross-functional teams (developers, data scientists, business) to implement enterprise GenAI solutions. Requires 4+ years of full-stack application development (Java, Python, JavaScript) and 3+ years with data structures, algorithms, and data stores. Stay current with AI research and communicate technical concepts to non-technical stakeholders.