4 days ago
Base Salary
$130k - $173k/yr
Responsibilities
- Design, build, and deploy LLM-powered tools for code generation, code review, debugging, refactoring, automated test creation, and documentation.
- Develop RAG pipelines grounded in codebases, requirements, design documents, standards, and domain knowledge.
- Create agentic workflows integrating engineering toolchains such as compilers, static analyzers, test frameworks, version control systems, and issue-tracking platforms.
- Evaluate models based on performance, cost, latency, licensing, and security requirements.
- Apply prompt engineering, fine-tuning, and parameter-efficient adaptation techniques.
- Optimize model deployment for secure, on-premises, air-gapped, and classified environments.
- Integrate AI capabilities into IDE experiences, CI/CD pipelines, merge-request checks, and software quality processes.
- Establish benchmarks, evaluations, and guardrails for accuracy, security, reliability, and usability.
- Support software assurance, traceability, and human accountability in certified software environments.
- Partner with software, systems, test, cybersecurity, and business teams to transition solutions into broader engineering adoption.
- Mentor others and help define how generative AI is scaled across engineering.
Requirements
- Bachelor’s degree in Computer Science, Software Engineering, or a related STEM field.
- At least 5 years of experience in software engineering, machine learning engineering, or a closely related technical field.
- Hands-on experience developing software solutions in production or operational environments.
- Active U.S. Government Security Clearance and U.S. citizenship, as required for maintaining the clearance.
- Strong Python programming skills and experience with modern ML/LLM frameworks such as PyTorch, Hugging Face Transformers, LangChain, or LlamaIndex.
- Experience building and deploying LLM applications such as RAG systems, AI coding assistants, copilots, or agent-based workflows.
- Working knowledge of C/C++ and embedded software development environments.
- Experience with vector databases, embeddings, search technologies, fine-tuning, quantization, and efficient inference serving.
- Experience integrating AI capabilities into DevSecOps and software engineering workflows.
- Familiarity with software assurance or certification considerations including DO-178C, MISRA, or CERT C/C++.
- Experience deploying solutions in secure, disconnected, or classified environments is preferred.
- A master’s degree, mission-critical industry experience, and knowledge of AI security, data governance, and responsible AI practices are preferred.
- Strong problem-solving, communication, and collaboration skills.
Benefits
- Comprehensive medical, dental, vision, and prescription drug benefits.
- Health Coach access and a 24/7 Employee Assistance Program.
- GE Aerospace Retirement Savings Plan, 401(k) with matching and company contributions, and Fidelity planning resources.
- Tuition assistance, adoption assistance, paid parental leave, disability insurance, life insurance, and paid time off.
- Annual discretionary bonus eligibility in addition to base pay.
- Onsite work in Grand Rapids, Michigan, with corporate relocation assistance provided.
- Posting expected to close on 12/30/26.
Categories
About GE
GE is a public industrial company that designs and sells aircraft engines, power generation equipment, and related software and services to airlines, utilities, and governments. Following its restructuring, it operates through GE Aerospace and GE Vernova. Founded in 1892 and headquartered in Boston, it trades on the NYSE as GE and serves global aviation and energy markets.