RTX Corporate is seeking an Applied AI Engineer to design, build, evaluate, and deploy production-grade AI, ML, and Generative AI solutions. This hybrid role applies retrieval and agentic approaches to deliver reliable AI system behavior and integrate AI capabilities into enterprise applications within secure and scalable production environments.
Role Overview
The position focuses on developing and operationalizing AI systems that use retrieval-augmented generation, agentic AI, and robust evaluation practices. The engineer will work across the lifecycle from experimentation to secure deployment, partnering with architecture, platform, data, evaluation, and cybersecurity teams to support enterprise business and engineering needs.
Responsibilities
- Design, develop, and deploy production-grade AI and ML solutions using combinations of traditional machine learning, Generative AI, retrieval-augmented generation, agentic AI, and software engineering.
- Build AI agents and intelligent workflows that reason, use tools, interact with enterprise applications and data, and execute complex multi-step processes with appropriate human oversight.
- Develop retrieval and context-engineering solutions using enterprise data, embeddings, vector and enterprise search, knowledge sources, prompts, memory, and other grounding techniques.
- Integrate AI solutions with enterprise applications, APIs, data sources, and tools, using standard interfaces and interoperability approaches such as Model Context Protocol (MCP).
- Evaluate and select models and solution approaches based on quality, reliability, latency, cost, security, scalability, and business requirements; develop systematic evaluation cases to measure solution performance.
- Develop production-quality software, APIs, integrations, tools, and reusable AI components to deliver end-to-end AI solutions while leveraging enterprise platform capabilities.
- Diagnose and improve AI system behavior using evaluations, traces, telemetry, user feedback, and failure analysis, addressing groundedness, task completion, robustness, and production reliability.
- Partner with AI Architecture, Platform Engineering, Data, Evaluation, Cybersecurity, and business teams to move solutions from experimentation into secure, scalable production environments.
Required Qualifications
- A University Degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a related STEM discipline and a minimum of 8 years of relevant professional experience, or an Advanced Degree in a related field and a minimum of 5 years of relevant professional experience.
- At least 3 years of hands-on experience developing, integrating, or deploying AI/ML solutions, including experience moving AI or ML capabilities beyond experimentation into production or production-like environments.
- Software engineering experience with hands-on programming in Python and development of production-quality, tested, maintainable software.
- Experience building applications using Generative AI and large language models, including prompt or context engineering, model integration, structured outputs, retrieval, or tool use.
- Experience integrating software with APIs, databases, enterprise applications, cloud services, or other external systems.
- Experience applying software development practices including source control, automated testing, CI/CD, containerization, and production deployment.
- Experience applying machine learning fundamentals, model evaluation, and tradeoffs involved in selecting and applying AI models to business problems.
Technologies
- Python
- Generative AI and large language models
- Retrieval-augmented generation, agentic AI
- Embeddings, vector databases, enterprise search
- Knowledge graphs
- Model Context Protocol (MCP)
- LangGraph, CrewAI
- IBM watsonx
- AWS Bedrock, Microsoft AI platforms
- n8n
- Docker, Kubernetes
- CI/CD and containerization
Compensation
$107,500 USD - $204,500 USD per year.
Work Location and Hybrid Schedule
Farmington, CT, United States (hybrid). Eligible candidates must reside within commuting distance of Farmington, CT, El Segundo, CA, San Jose, CA, Tucson, AZ, McKinney, TX, Andover, MA, Cedar Rapids, IA, or Charlotte, NC.
Hybrid roles work regularly both onsite and offsite, with the onsite ratio determined in partnership with your leader.
Benefits
- Healthcare, wellness, retirement and work/life benefits
- Parental leave (including paternal leave)
- Flexible work schedules
- Achievement awards
- Educational assistance
- Child/adult backup care
- Medical, dental, vision, life insurance
- Short-term disability, long-term disability
- 401(k) match
- Flexible spending accounts
- Employee assistance program
- Employee Scholar Program
- Paid time off and holidays
- Annual short-term and/or long-term incentive compensation programs (depending on level and coverage)
U.S. Person Requirement
This job requires a U.S. Person. A U.S. Person is a lawful permanent resident as defined in 8 U.S.C. 1101(a)(20) or a protected individual as defined in 8 U.S.C. 1324b(a)(3). U.S. citizens, U.S. nationals, U.S. permanent residents, and individuals granted refugee or asylee status in the U.S. are considered U.S. persons.
Security Clearance
- Security clearance type: None/Not Required
- Security clearance status: Not Required
