Managing Software Engineer - Senior Gen AI/Agentic Engineer
US-TX-Dallas
Capgemini
A global leader in consulting, technology services and digital transformation, we offer an array of integrated services combining technology with deep sector expertise.Description
About the job you’re considering
Job Description
We are seeking a creative and innovative Senior GenAI /Agentic Engineer to join our team. This role involves developing cutting-edge custom GEN AI solutions and predictive AI models, deploying them in production environments, and driving the integration of AI technologies across our business operations. As a key member of our AI team, you will collaborate with diverse teams to design solutions that deliver tangible business value through AI-driven insights
Your role
Gen AI & Machine Learning Models Development
• Design, develop, and implement both generative and predictive AI models (including NLP, computer vision, etc.).
• Lead the development of innovative solutions such as intelligent autonomous agents for complex tasks and multimodal interactions.
• Integrate agentic workflows that utilize AI agents to automate tasks and improve operational efficiency.
• Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to align AI solutions with business objectives.
Application Architecture Design, Development, & Integration
• Demonstrates proficiency in API architecture and design to develop custom generative AI applications built with external interfacing, traffic control, runtime execution of business logic, data access, authentication, and deployment components.
• Work with cloud platforms (e.g., Azure, AWS, GCP) and big data tools (e.g., Databricks, PySpark) to develop AI solutions.
• Optimize AI models and algorithms for performance, scalability, and efficiency.
• Ensure the security and compliance of AI solutions, adhering to best practices and regulations.
• Implement monitoring and logging mechanisms to track performance, reliability, and usage of AI solutions
Model Deployment & Maintenance
• Work closely with DevOps and IT teams to deploy AI models into production environments, ensuring scalability, performance, and optimization.
• Monitor and troubleshoot deployed models and pipelines for optimal performance.
• Design and maintain data pipelines for efficient data collection, processing, and storage (e.g., data lakes, data warehouses).
• Create comprehensive documentation for deployment processes and provide training to relevant teams to ensure proper model management.
AI Research & Integration
• Conduct research to stay at the forefront of emerging AI techniques, tools, and trends.
• Integrate new AI tools and methodologies into existing business processes and applications.
• Lead the development of private GenAI tools, including LLMs and specialized AI use cases.
Collaboration & Communication:
• Collaborate with cross-functional teams to align AI projects with business requirements and strategic goals.
• Lead and contribute to GenAI and AI business development efforts such as capability pitches, demos, proposals, and overall project planning.
• Communicate complex AI concepts and results to non-technical stakeholders.
• Lead and mentor a small team of junior engineers and data scientists.
Your skills and experience
- Skilled in constructing agentic systems through techniques such as multi-agent systems, reinforcement learning, dynamic workflows, caching/memory management, and concurrent orchestration.
- Demonstrated excellence in Agentic AI architecture, encompassing development, testing, and research of GenAI agents, utilizing current-generation deployments and pioneering next-generation patterns and research.
- Proficient in various AI and Agentic AI frameworks, including LangChain/LangGraph, Crew AI, Semantic Kernel or Open AI Agentic SDK.
- Strong skills in prompt engineering and its techniques including design, development, and refinement of prompts (zero-shot, few-shot, and chain-of-thought approaches) to maximize accuracy and leverage optimization tools.
- Proficiency in programming languages such as Python and SQL, as well as machine learning libraries like TensorFlow, PyTorch, and scikit-learn.
- Proficiency in URLs and API Endpoints, HTTP Requests, Authentication Methods, Response Types, JSON/REST, Parameters and Data Filtering, Error Handling, Debugging, Rate Limits, Tokens, Integration, and Documentation.
- Experience with cloud platforms (e.g., AWS, Azure) and big data tools (e.g., Databricks, PySpark).
- Knowledge of deployment tools (e.g., Azure DevOps, Docker, AWS ECS/EKS/Fargate) and CI/CD pipelines (AWS CloudFormation, CodeDeploy).
- Strong understanding of data engineering principles, including experience with SQL and NoSQL databases (e.g., MySQL, MongoDB, Redis).
Life at Capgemini
Capgemini supports all aspects of your well-being throughout the changing stages of your life and career. For eligible employees, we offer:
- Flexible work
- Healthcare including dental, vision, mental health, and well-being programs
- Financial well-being programs such as 401(k) and Employee Share Ownership Plan
- Paid time off and paid holidays
- Paid parental leave
- Family building benefits like adoption assistance, surrogacy, and cryopreservation
- Social well-being benefits like subsidized back-up child/elder care and tutoring
- Mentoring, coaching and learning programs
- Employee Resource Groups
- Disaster Relief
About Capgemini
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to
engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2024 global revenues of €22.1 billion.
Get the future you want | www.capgemini.com
Disclaimer
Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodations do not pose an undue hardship.
Capgemini is committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.
Click the following link for more information on your rights as an Applicant http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law
Applicants for employment in the US must have valid work authorization that does not now and/or will not in the future require sponsorship of a visa for employment authorization in the US by Capgemini.
Job
: Project ManagerSchedule
: Full-timePrimary Location
: US-TX-DallasOrganization
: I&D* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Architecture AWS Azure Big Data CI/CD CloudFormation Computer Vision Databricks Data pipelines DevOps Docker ECS Engineering GCP Generative AI JSON LangChain LLMs Machine Learning ML models Model deployment MongoDB MySQL NLP NoSQL Pipelines Prompt engineering PySpark Python PyTorch Reinforcement Learning Research Scikit-learn Security SQL TensorFlow Testing
Perks/benefits: Career development Flex hours Flex vacation Health care Parental leave
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