Build, enhance, and support production generative AI applications and web-based AI solutions for the Centers for Disease Control and Prevention (CDC).
Compensation
Estimated Salary/Wage
USD $82,000.00/Yr. Up to USD $118,000.00/Yr.
Responsibilities
Build, enhance, and support production generative AI applications and web-based AI solutions
Develop Python backend services and AI integrations using Azure OpenAI, Azure AI Foundry, and related Azure services
Implement RAG pipelines, including document processing, chunking, embeddings, search, context preparation, and source citations
Implement agent workflows using tool/function calling, structured outputs, conversation context, error handling, execution limits, and human review where needed
Integrate AI applications with APIs, enterprise data sources, databases, cloud services, and MCP-based tools
Requirements
Bachelor’s degree in computer science, engineering, or a related field
Own end-to-end solution architecture across Agentforce, Salesforce CPQ and Revenue Cloud Advanced.
Responsibilities
Own end-to-end solution architecture across Agentforce, Salesforce CPQ and Revenue Cloud Advanced
Architect agent-assisted and agentic workflows across opportunity, configuration, pricing, quoting, contracting, ordering and revenue lifecycle processes
Design agent orchestration patterns, including tool/function calling, workflow delegation, multi-agent patterns, state management and memory
Architect integration of Agentforce with Salesforce automation, Apex, Flow, APIs, MuleSoft and external enterprise services
Define appropriate use of LLMs, deterministic logic, workflow engines and traditional automation, rather than defaulting all use cases to generative AI
Requirements
Nice to have: Salesforce Application/System/Technical Architect credentials
Nice to have: Agentforce and Revenue Cloud-related certifications
Design, develop, and maintain backend services using Python, build and optimize RESTful APIs and microservices, and work with cloud platforms such as Microsoft Azure or GCP.
Responsibilities
Design, develop, and maintain backend services using Python
Build and optimize RESTful APIs and microservices
Work with Microsoft Azure (priority) or GCP to design, deploy, and manage cloud solutions
Implement CI/CD pipelines and automated testing workflows
Work with Docker and Kubernetes in production environments
Senior technical leader responsible for architecting, building, and scaling enterprise-grade AI, automation, and full-stack solutions across Finance.
Responsibilities
Lead the architecture, design, development, and delivery of enterprise-grade AI, automation, and full-stack solutions across Finance
Build production applications end to end across user experience, APIs, backend services, data, AI/agents, automation, enterprise integrations, and cloud infrastructure
Design and implement Generative AI and agentic AI solutions, including RAG, tool/function calling, AI agents, workflow orchestration, and human-in-the-loop experiences
Build scalable full-stack applications using Angular/React, TypeScript, Python/FastAPI, Java/Spring Boot, APIs, microservices, and modern data platforms
Modernize traditional automation toward API-first, event-driven, AI-enabled, and agentic architectures
Requirements
Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Engineering, or related field
Define the product and technology strategy and roadmap for the company's AI productivity / Agent platform, and own the end-to-end employee technology experience across collaboration tools, knowledge systems, identity and access, workplace technology, IT service platforms and AI productivity tools.
Responsibilities
Define the product and technology strategy and roadmap for the company's AI productivity / Agent platform
Build scalable Agent capabilities including orchestration, tool integration, memory/context management, evaluation, observability, security and governance
Lead teams through 0-to-1 and 1-to-10 product development, rapidly moving high-priority use cases from prototype to production
Establish reusable platform capabilities, engineering standards, connectors and governance
Identify internally proven capabilities that can potentially be developed into products or platform services for external customers, partners or ecosystems
As a Test Manager in PEU-RP you will as a technical leader develop and use agentic AI as tool to drive and define test analysis of new 5G and 6G RAN features, to secure the most efficient and effective testcoverage, which ensures product quality and an optimized product flow.
Compensation
The salary range for this position is
• Ottawa: $101,500CAD - $ 133,350CAD
Short-Term Variable Compensation Plan: Your pay also includes the opportunity for an annual bonus. Actual bonus payouts are based on performance of the business against the unit’s objectives, individual performance, and the individual bonus target. Certain eligibility and pro-ration rules apply.
Responsibilities
Drive test analysis of 5G and 6G RAN features from study through execution: set and communicate test scope, and secure test coverage and quality.
Identify the impact and risks of new features on test tools, forecast test environment requirements and follow up their implementation.
Drive the design, development and deployment of Agentic AI solutions for test, such as AI agents for test analysis, test case selection and generation and etc
Deploy, operate and scale AI solutions on AWS or other cloud platforms, in close collaboration with tools, CI/CD and infrastructure teams
Educate and support the organization on test strategy, efficient testing and the use of AI agents in the test flow
Requirements
M.Sc/B.Sc in Telecommunication/Electrical Engineering /Computer Science or equivalent experience
Nice to have: Production-grade AI engineering practice
Esta posición actúa como un puente entre la genética cuantitativa, el mejoramiento genético y la Inteligencia Artificial, transformando datos experimentales, genéticos, ambientales y operativos en modelos y soluciones que fortalezcan la toma de decisiones.
Responsibilities
Conectar metodologías de genética cuantitativa y mejoramiento genético con herramientas de Inteligencia Artificial, asegurando que los modelos sean estadísticamente robustos, reproducibles y relevantes para las decisiones de selección y posicionamiento
Desarrollar modelos estadísticos aplicados a la selección y al posicionamiento de genotipos e híbridos
Analizar datos experimentales de campo mediante metodologías avanzadas, con foco en la interacción genotipo × ambiente
Revisar los procesos actuales e identificar oportunidades para la aplicación de IA, automatización y soluciones basadas en agentes
Diseñar e implementar soluciones analíticas que integren datos experimentales, genéticos, ambientales y operativos
Requirements
Maestría o Doctorado en Estadística, Mejoramiento Genético, Biología, Genética Cuantitativa, Ciencia de Datos, Ciencia de la Computación, Bioestadística o áreas afines
Nice to have: Conocimiento de LLMOps, evaluación y monitoreo de soluciones de IA, gobernanza, control de acceso y trazabilidad
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status
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