Applied AI Engineer (Hybrid)
RTX Corporation1 day ago
Charlotte, NC, USA or San Jose, CA, USASenior
Base Salary
$108k - $205k/yr
Responsibilities
- Design, develop, evaluate, and deploy production-grade AI and machine learning solutions using traditional ML, Generative AI, retrieval-augmented generation, agentic AI, and software engineering.
- Build AI agents and intelligent workflows that use tools, enterprise applications, data, memory, and human oversight to execute complex multi-step processes.
- Develop retrieval and context-engineering solutions using embeddings, vector and enterprise search, knowledge sources, prompts, and grounding techniques.
- Integrate AI solutions with enterprise applications, APIs, data sources, and tools using interfaces such as Model Context Protocol.
- Evaluate models and solution approaches for quality, reliability, latency, cost, security, scalability, and business fit, and develop systematic evaluation cases.
- Develop production-quality software, APIs, integrations, tools, and reusable AI components for end-to-end solutions.
- Diagnose and improve AI system behavior using evaluations, traces, telemetry, feedback, and failure analysis.
- Collaborate with architecture, platform engineering, data, evaluation, cybersecurity, product, business, and other engineering teams to move solutions into secure production environments.
Requirements
- A university degree in computer science, artificial intelligence, machine learning, engineering, or a related STEM discipline plus at least 8 years of relevant professional experience, or an advanced degree in a related field plus at least 5 years of relevant professional experience.
- At least 3 years of hands-on experience developing, integrating, or deploying AI/ML solutions into production or production-like environments.
- Hands-on Python programming and experience developing tested, maintainable, production-quality software.
- Experience building Generative AI and large language model applications, 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 with source control, automated testing, CI/CD, containerization, production deployment, machine learning fundamentals, and model evaluation.
- Preferred experience with production AI agents, agentic or multi-agent workflows, retrieval-augmented generation, embeddings, vector databases, enterprise search, knowledge graphs, and advanced context engineering.
- Preferred experience with LangGraph, CrewAI, IBM watsonx, AWS Bedrock, Microsoft AI platforms, n8n, Model Context Protocol, function or tool calling, evaluation frameworks, tracing, observability, guardrails, monitoring, traditional ML, model serving, model lifecycle management, MLOps, Docker, Kubernetes, and cloud-native or hybrid deployment.
- Ability to independently solve complex technical problems, collaborate across disciplines, and communicate technical concepts and tradeoffs effectively.
- Must be a U.S. Person as defined in the posting and able to work in a U.S.-based hybrid role within commuting distance of an approved location.
Benefits
- Hybrid work arrangement with regular onsite and offsite work; 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.
- Healthcare, wellness, retirement, life insurance, disability coverage, 401(k) match, flexible spending accounts, paid time off, and holidays.
- Flexible work schedules, parental leave, employee assistance, educational assistance, Employee Scholar Program, recognition programs, achievement awards, and child/adult backup care.
- Potential eligibility for annual short-term or long-term incentive programs, depending on position and business unit.
Tech Stack
Categories
About RTX Corporation
RTX Corporation builds aerospace and defense systems through its Collins Aerospace, Pratt & Whitney, and Raytheon businesses, serving commercial aviation, the U.S. government, and allied militaries. Its products range from aircraft engines and avionics to radars, missiles, and command-and-control software, sold via long-term OEM programs and defense contracts. Formed in 2020 by the Raytheon–United Technologies merger, RTX is headquartered in Arlington, Virginia and trades on the NYSE as RTX.