Advanced Software Engineer, Forward Deployed (AI Reliability Engineering)
Posted yesterday
The role in short
Embed with operations teams to design, build, and deploy custom AI-native software solutions and data integrations for manufacturing workflows.
Basic Qualifications
Bachelor's degree in Software Engineering, or related Science, Technology, Engineering or Mathematics field, plus a minimum of 5 years of relevant experience; or Master's degree, plus 3 years relevant experience.
Due to the nature of work performed within our facilities, U.S. citizenship is required.
Responsibilities for this Position
Imagine a world-class engineering environment. Now add a team of exceptional talent along with technologies that are so advanced they’re often classified. That’s what you’ll find at General Dynamics Mission Systems. Here you’lljoin a team of exceptional engineers as they invent the technologies, products and services that help our service members, intelligence analysts and first responders keep our nation safe. If you want the chance to build things that matter, it’s time to bring your talent to General Dynamics Mission Systems.
We apply advanced technologies such as Artificial Intelligence, Blockchain, AR/VR, Cloud Native and Quantum Physics to solve our customers’ missions in cyber, RF, undersea, interstellar and everything in between.
You will be part of the Operations Technology team, a forward deployed engineering group that embeds directly with users to understand workflows, define requirements, and build custom AI-native solutions from scratch. You will work across the full development lifecycle: gathering requirements firsthand from operators and engineers on the manufacturing floor, designing scalable architectures, writing and shipping production code, and supporting the systems you build. The scope spans software, data architecture, and emerging manufacturing technologies including Agentic AI, IoT, machine learning, robotics, computer vision, digital twins, and more. Our team builds purpose-built systems that replace legacy applications and establish a connected data foundation across the enterprise.
Key Responsibilities:
Software Development & Deployment:
- Design, develop, test, and deploy full-stack web applications for manufacturing execution, data integration, and operational intelligence
- Build AI-native applications with intelligence embedded from the architecture up
- Develop APIs, data pipelines, and integration layers that connect business systems into a unified data architecture
- Write clean, scalable code with a focus on enterprise-scale deployment across all operations sites
- Deploy in weeks, not months, using modern development tools including AI coding assistants
Forward Deployed Engineering:
- Embed directly with operations users at GDMS sites to understand workflows and define requirements firsthand
- Own problems end to end: requirements, design, development, deployment, and support
- Translate complex business processes into working software through rapid prototyping and iterative delivery
- Build for the user, not the specification. The user's experience matters more than the feature list.
Data Architecture & Integration:
- Design data models that capture, normalize, and flow operations data into a central data warehouse
- Build integrations between enterprise systems (ERP, PLM, MES, and other business applications)
- Eliminate shadow data by building systems that capture critical manufacturing data digitally at the point of work
AI & Emerging Technology:
- Embed AI/ML capabilities into applications: predictive quality, anomaly detection, natural language data access, autonomous decision support
- Leverage large language models and AI coding agents as core tools in the development workflow
- Explore and evaluate emerging manufacturing technologies (IoT, robotics, digital twins, computer vision) for integration into the team's technology roadmap
- Identifies opportunities to apply AI for continuous improvement and innovation
Cross-Functional Collaboration:
- Partner with Manufacturing, Supply Chain, Quality, Facilities, EH&S, Government Property, and all Operations personnel across multiple sites
- Work closely with IT infrastructure teams on cloud deployment, security compliance, and DevSecOps practices
- Communicate technical concepts clearly to non-technical stakeholders
Qualifications Required:
- Bachelor's degree in Computer Science, Software Engineering, or a related field
- Proficiency in Python and/or JavaScript/TypeScript with full-stack development experience
- Experience with web application frameworks, relational databases, and REST API design
- Strong understanding of modern development practices (DevOps, Agile, CI/CD)
- Demonstrated ability to work independently and take ownership of deliverables in a fast-paced environment
- Strong problem-solving and communication skills
Preferred:
- Experience building AI/ML capabilities or LLM-based applications
- Proficiency with AI coding assistants (Claude Code, Copilot, Cursor) in professional workflows
- Experience with cloud platforms (Azure, AWS) and containerization (Docker, Kubernetes)
- Familiarity with manufacturing systems (MES, ERP) or industrial data integration (OPC-UA, MQTT)
- Experience in defense or aerospace industries
Our Commitment to You:
- An exciting career path with opportunities for continuous learning and development.
- Research oriented work, alongside award winning teams developing practical solutions for our nation’s security
- Flexible schedules with every other Friday off work, if desired (9/80 schedule)
- Competitive benefits, including 401k matching, flex time off, paid parental leave, healthcare benefits, health & wellness programs, employee resource and social groups, and more
- See more at gdmissionsystems.com/careers/why-work-for-us/benefits
Workplace Options:
This position is a remote position
Salary Note
This estimate represents the typical salary range for this position based on experience and other factors (geographic location, etc.). Actual pay may vary. This job posting will remain open until the position is filled.
Combined Salary Range
USD $118,519.00 - USD $131,482.00 /Yr.
Company Overview
General Dynamics Mission Systems (GDMS) engineers a diverse portfolio of high technology solutions, products and services that enable customers to successfully execute missions across all domains of operation. With a global team of 12,000+ top professionals, we partner with the best in industry to expand the bounds of innovation in the defense and scientific arenas. Given the nature of our work and who we are, we value trust, honesty, alignment and transparency. We offer highly competitive benefits and pride ourselves in being a great place to work with a shared sense of purpose. You will also enjoy a flexible work environment where contributions are recognized and rewarded. If who we are and what we do resonates with you, we invite you to join our high-performance team!
Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans
Prep for this interview
5 questions likely to come up at General Dynamics Mission Systems, each matched to a line in this posting.
- 1Cloud, deployment and security
They wrote: “Experience with cloud platforms (Azure, AWS) and containerization (Docker, Kubernetes)”
How would you debug a deployment that works in staging but fails at the customer's site?
How to answer
Why they ask: Customer environments differ in ways you can't see. This tests method under pressure.
- Compare versions, config and environment variables
- Check network rules, proxies and certificates (common in enterprise)
- Look at resource limits and permissions
- Add the missing check to your install steps afterwards
Tip: List the usual suspects and how you'd check each without full access.
- 2Integrations and APIs
They wrote: “Develop APIs, data pipelines, and integration layers that connect business systems into a unified data architecture”
Walk me through connecting our product to a customer's internal system that has no documentation.
How to answer
Why they ask: This happens weekly in the job. They want a calm, step-by-step method.
- Find who owns the system and get read access to a test environment
- Watch real traffic or logs to learn the data shapes
- Build a thin adapter with logging around every call
- Agree on how failures get reported, and who fixes what
Tip: Talk about finding the owner of the system first. The code is the easy part.
- 3Data and SQL
They wrote: “Design data models that capture, normalize, and flow operations data into a central data warehouse”
The customer's data is spread across five systems that disagree. How do you get one clean view?
How to answer
Why they ask: Real deployments rarely have one source of truth. They want a practical approach, not a perfect one.
- List each system and what it's the best source for
- Pick matching keys and decide how to handle records that don't match
- Load into one place with clear rules, and keep the raw copies
- Show the customer the mismatches; they often fix the source
Tip: Name the system the business trusts most for each field, and get the customer to agree.
- 4Coding
They wrote: “Proficiency in Python and/or JavaScript/TypeScript with full-stack development experience”
Here's a CSV export from a customer. Write a script that cleans it and loads it into our API.
How to answer
Why they ask: Very close to real FDE work. They watch how you handle bad rows and failures.
- Read with a proper CSV parser; check the header first
- Validate each row and collect errors, not crash on the first one
- Send in batches with retries and a clear report at the end
- Write one or two quick tests for the parsing
Tip: Talk through edge cases out loud: encodings, missing fields, duplicates, rate limits.
- 5Discovery and scoping
They wrote: “Embed directly with operations users at GDMS sites to understand workflows and define requirements firsthand”
A customer says “we want AI in our claims process.” What do you ask in the first meeting?
How to answer
Why they ask: Most FDE work starts this vague. They want to hear you find the real problem before you pick a tool.
- Map the current process: who touches a claim, in what order, with which systems
- Find the slowest or most error-prone step and ask what it costs them
- Agree on one measurable goal (for example time per claim, or error rate)
- Ask what data you can access, and who signs off on security
Tip: Ask about the work, not the technology. Who does it today, how long it takes, what a mistake costs, and how they'd know it got better.
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