Top Tech Jobs & Startup Jobs in Austin, TX

Leads the architecture and development of Java-based enterprise applications, microservices, REST APIs, and cloud solutions on AWS. Develops applied generative AI solutions using LLMs, RAG, fine-tuning, prompt engineering, and managed platforms such as AWS Bedrock. Guides application design, deployment, security, monitoring, performance, and technical implementation while collaborating with project teams. The role is fully onsite in McLean, Virginia and requires extensive experience with modern Java, cloud-native technologies, containers, UI frameworks, and AI development.

Senior Business Analyst responsible for translating accounting and financial-services processes into business and technical requirements. The role supports application modernization, legacy migration, cloud adoption, process modeling, stakeholder workshops, solution design, UAT, defect triage, and Agile or Waterfall SDLC delivery. Strong accounting knowledge, SQL and data analysis skills, IT ecosystem understanding, and experience with modernization initiatives are required.

Designs, develops, and supports supply chain reporting, analytics, and AI-assisted workflow solutions. Responsibilities include building Power BI dashboards, Snowflake data and semantic models, DAX measures, Power Query transformations, KPI visualizations, workflow solutions, data validation, technical documentation, deployment support, and stakeholder engagement across procurement, inventory, warehousing, logistics, and supplier processes.

Leads performance testing across projects, designing and executing scripts with JMeter and LoadRunner. Analyzes results, creates reports and dashboards, configures testing tools, and provides performance insights to stakeholders. The role requires expertise in load, stress, and capacity testing, web and database protocols, performance monitoring tools, and strong leadership and communication skills.

Technical Architect role listed as a replacement position. The description provides no details about responsibilities, required technologies, qualifications, compensation, travel, or clearance requirements.

Designs, develops, deploys, and supports enterprise API solutions using Apigee and Kubernetes. Responsibilities include managing API proxies and lifecycles, implementing API security, deploying microservices and containerized workloads, maintaining Kubernetes resources, automating CI/CD pipelines, monitoring performance, troubleshooting production issues, and implementing observability. The role collaborates with developers, architects, and stakeholders to deliver scalable, secure, and reliable cloud-native platforms.

Implement, support, and troubleshoot ServiceNow Discovery across enterprise environments. Manage MID Servers, Discovery Patterns, Sensors, IRE, CMDB Health, credentials, performance, and cloud resource discovery across AWS, Azure, and GCP. Develop Python automation and use AI-assisted development tools. Support ServiceNow solutions hosted primarily on AWS, participate in live technical interviews, maintain a ServiceNow PDI, and complete background, employment, and certification verification.

Develop and enhance Salesforce solutions using declarative tools, Apex, LWC, asynchronous processing, SOQL/SOSL, APIs, and Salesforce DX. Provide production support, estimate and design enhancements, and lead offshore team members supporting implementations and users.

Leads the design and development of enterprise-wide data and analytics systems using Snowflake, Python, advanced SQL, and AWS services including Lambda, Step Functions, and ECS. Requires strong data engineering expertise and practical experience building modern platforms within financial services, with knowledge of asset management and financial markets.

Develop generative AI solutions using Python, AWS, LLMs, chatbots, prompt and context engineering, RAG, vector databases, and agentic AI frameworks. Build coding prompts and contexts with GitHub Copilot, Claude Code, and Amazon Q Developer to convert business stories into production code and pull requests. Design autonomous and multi-agent workflows, memory and token-management systems, caching strategies, MCPs, and real-time AI decisioning features. Auto-lending experience and A/B testing expertise are advantageous.