AI Engineer Software (Level 2 or 3)

Northrop Grumman•El Segundo, CA

3d•$111,000 - $206,800•Onsite

About The Position

At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history - from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon. We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work — and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history. This requisition may be filled at the Level 2 or Level 3 based on requirements listed below. The Northrop Grumman Aeronautics Sector in Space Park Redondo Beach/El Segundo, CA is seeking a highly motivated AI Software Engineer to join our team. Our AI team is growing and there is an opportunity to work closely with senior AI subject matter experts while simultaneously supporting the business. We are looking for a talented AI Software Engineer who can take small to medium sized projects from concept to production quickly with limited technical guidance. You will build and fine‑tune Retrieval‑Augmented Generation (RAG) pipelines, Agentic AI pipelines, and large language model (LLM) solutions that solve concrete business problems. You will work closely with product owners, data scientists, and senior engineers to ship reliable, scalable AI services. Successful candidates will have demonstrated the ability to build AI solutions to solve customer problems. They will have a track record as an effective communicator and problem solver who is able to develop and maintain good working relationships with internal and external stakeholders. The selected candidates will work closely with AI engineers and business partners to accomplish the following:

Requirements

For level 2 consideration: Bachelor's degree in Computer Science or related STEM field and 2 years of relevant experience or Master's degree in Computer Science or related STEM field with relevant entry level experience
For Level 3 consideration: Bachelor's degree in Computer Science or related STEM degree and 5 years with Master's degree in Computer Science or related STEM field and 3 years of relevant experience
Entry level professional AI/software engineering experience; demonstrated ability to ship production-grade code
Ability to obtain and maintain final US Government Secret Clearance
Must have ability to obtain and maintain Program Access (PAR) within a reasonable period of time, as determined by the company to meet its business needs
Strong problem‑solving skills and ability to work independently on moderately scoped projects.
Demonstrated ability to carry out rapid prototyping and proof-of-concept demonstrations using novel AI methods to solve real-world challenges.
Ability to effectively communicate system properties and results to technical staff as well as non-technical management and leadership stakeholders.
Proficiency in Python (including libraries such as PyTorch, Hugging Face Transformers, LangChain, LangGraph).
Familiarity with RAG and agentic AI concepts: vector stores (e.g., Pinecone, FAISS, Milvus), embeddings, similarity search, prompt engineering, function calling or tool use, structured outputs
Experience developing AI solutions using LLMs, Agentic AI, MLOps pipelines, Cloud services, ETL, evaluation of AI solution, services, containers and container orchestration
Hands‑on experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
Understanding of software engineering best practices: version control (Git), CI/CD pipelines, automated testing, code reviews.

Nice To Haves

Active and final US Government Secret Clearance
Ability to obtain and maintain a U.S. Government Top Secret security clearance (U.S. citizenship is a pre-requisite)
Experience working with DoD/DoW customer
Experience building and training large neural networks on custom datasets
Strong understanding of neural network fundamentals, including model architectures, loss functions, optimization, regularization, and evaluation methodologies
Experience with supervised learning, unsupervised learning, reinforcement learning, and statistical modeling
Experience with deep learning frameworks (PyTorch, TensorFlow, JAX)
Experience working in Agile software development environment
Experience with leading teams and actively participating in the development of winning white papers and proposals for DoD customers
Familiarity with explainable AI, adversarial AI, responsible AI (NIST AI Risk Framework)
Familiarity with signal processing, information theory, topological data analysis, and/or genetic algorithms.

Responsibilities

Work with customers to define, develop, and deliver AI solutions to meet mission and sector needs.
Design, develop, document, test and debug applications software and systems that contain logical and mathematical solutions.
Collaborate with cross-functional teams to deploy machine learning algorithms for testing and is in production systems.
Maintain understanding of the cutting-edge technologies in AI/ML.
Regularly demonstrate progress to customers.
Rapidly prototype and deliver – Turn medium‑priority use‑case specifications into working AI prototypes within 2‑4 weeks and iterate to production quality.
RAG, Agentic AI, and LLM Development – Design and implement retrieval‑augmented generation pipelines and agentic workflows integrating pretrained LLMs (e.g., GPT‑4/5/OSS, Llama) though APIs and self-hosted model deployments.
Model Integration – Embed fine‑tuned models into existing micro‑service architectures (REST/GraphQL, gRPC) and expose them via APIs or internal SDKs.
Performance & Reliability – Set up monitoring, logging, and automated testing (unit, integration, latency) for AI services; troubleshoot model drift and latency issues.
Data Preparation – Collaborate with data engineers to curate, clean, and annotate domain‑specific datasets for fine‑tuning and evaluation.
Documentation & Knowledge Sharing – Write clear technical documentation, create example notebooks, and mentor junior teammates on AI best practices.
Continuous Improvement – Stay current with the latest LLM research, open‑source tools, and industry trends; propose upgrades to the AI stack.

Benefits

Relocation assistance may be available
health insurance coverage
life and disability insurance
savings plan
Company paid holidays and paid time off (PTO) for vacation and/or personal business
overtime
shift differential
discretionary bonus
Annual bonuses
Long Term Incentives (for VP or Director positions)