Senior hands‑on technical leader responsible for architecting, engineering, and delivering enterprise‑scale GenAI and Intelligent Automation solutions across cloud and enterprise AI platforms.
Locations (2)
Dallas, Texas, United States
Farmers Branch, Texas, United States
Responsibilities
Architect and deliver scalable, secure, resilient GenAI, RAG, Agentic AI, Document AI, and Virtual Assistant solutions.
Provide hands‑on leadership across architecture, design, prototyping, coding, deployment, troubleshooting, and production support.
Design, develop, and maintain software components for Mutual Funds Middle Office, supporting AI-related projects and ensuring quality deliverables.
Compensation
Expected base pay rates for the role will be between $136,000 and $136,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.
Responsibilities
Implement, design, and develop components of software projects within Mutual Funds Middle Office
Support AI-related mutual funds projects
Design and code reviews for software applications and projects
Utilize analytical and problem-solving skills to analyze database programs
Develop various aspects of software applications including UI, mid-tier services, and databases
Lead technical delivery for Air Force Research Laboratory Space Warfare Directorate, managing teams, processes, and client relationships while ensuring secure coding and mission-critical system integration.
Compensation
Salary range: $135,000.00 - $150,000.00
Responsibilities
Manage and lead team and overall processes for planning, execution and reporting
Perform administrative functions for workforce at Kirtland and assist FSO in onboarding and offboarding employees
Lead and manage subcontract efforts with potential prime contractor at AFRL and Space Force
Serve as software expert in coding scientific algorithms into operational applications
Manage source configuration management, software builds, tests, and application deployment
Design, develop, and operate scalable, secure, and reliable enterprise applications that drive business success.
Compensation
The annual base salary range for this position is $130,138 - $178,650. SAP believes the value of pay transparency contributes towards an honest and supportive culture and is a significant step towards demonstrating SAP’s commitment to pay equity. SAP provides the annualized compensation range inclusive of base salary and variable incentive target for the career level applicable to the posted role. The targeted combined range for this position is $130,138 - $198,500.
Responsibilities
Ensure delivery of high-quality, scalable, and secure solutions through efficient coding, testing, and collaboration with cross-functional teams
Design scalable, secure, and high-performing applications
Develop, test, deploy, deliver, and maintain applications
Conduct code reviews
Collaborate with product, design and cloud operations to define, design, and ship new features
Requirements
Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field
Master’s degree in Computer Science, Engineering, Information Technology, or a related field
Nice to have: AI Agent and AI Assisted development
Build, enhance and support digital products for the Driving School team, developing high-quality, scalable solutions using JavaScript, TypeScript, React, Node.js and GraphQL.
Responsibilities
Design, build and maintain high quality, scalable and well tested software across our digital products
Take ownership of features from analysis and design through to development, testing and delivery
Work closely with Product and business teams to understand requirements and deliver effective customer focused solutions
Help maintain the stability and performance of applications across our development and production environments
Contribute to engineering standards, testing practices, code quality and continuous improvement across the team
This role is designed for fresh graduates who are passionate about leveraging artificial intelligence and modern software development practices to deliver enterprise-grade solutions. You will work at the frontier of AI-enabled development, integrating generative AI tools and LLM technologies into real software systems.
Responsibilities
Design, build, and validate end-to-end AI-enabled solutions using coding assistants (GitHub Copilot, Claude, Gemini) and LLM APIs, with rigorous verification for security, performance, and production fitness
Collaborate across engineering, product, and business teams to deliver practical business outcomes; document design decisions, assumptions, and validation approaches for all AI-enabled features
Master prompt engineering and structured interaction techniques to extract reliable, contextual outputs from generative AI systems for real-world engineering and business use cases
Apply SDLC best practices, Agile/Scrum methodologies, and DevOps principles within fast-changing, AI-augmented environments
Participate across the full solution lifecycle—problem framing, design, integration, testing, deployment, monitoring, and support, ensuring code quality and security hygiene throughout
Requirements
Bachelor's degree (B.E./B.Tech) in Computer Science, Information Technology, or related engineering discipline
As a Lead Data Engineer, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way.
Responsibilities
Design, build, and operate production-grade data pipelines that ingest, clean, transform, and aggregate data from disparate sources to deliver trusted data products
Evolve logical and physical data models that create a comprehensive view of user flows, system dependencies, resiliency signals, and risk measures, and develop new models that support prediction and decisioning where appropriate
Translate business, risk, and control requirements into implementable technical designs and a pragmatic delivery plan, partnering with architects, data engineers, analysts, and stakeholders across a matrix organization.
Contribute to the broader data architecture strategy that underpins resiliency analytics and risk modeling, including integration and interoperability across data sources and systems
Implement and continuously improve data quality management, metadata management, and data governance practices to increase reliability, explainability, and auditability, and enable data lineage and traceability across sources, transformations, and curated outputs
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