Forward Deployed Industrial Engineer, Defense Logistics AI

Job Description

Job Description

Tagup is a defense technology company founded at MIT that is delivering logistics decision advantage with next-generation AI. We’re growing rapidly and are looking for change-makers passionate about delivering innovative technologies to solve the most challenging problems in the world’s highest stakes environments. This is an exciting opportunity to engage in meaningful work that strengthens national security and contributes to the success of U.S. and allied forces. Join us in shaping the future of defense logistics for a safer tomorrow.

The Marine Corps moves people, parts, and equipment around the world on timelines that don't forgive guesswork. We build the AI systems that help them do it — reinforcement learning–based planning and optimization software deployed inside real military logistics operations, from Marine Logistics Groups to Blount Island Command.

This role sits at the seam between our software and the operations it runs on. You'll be the person who turns messy, real-world logistics and maintenance data into the signal that drives both better day-to-day decisions for our customers and a smarter product for everyone who comes after them. If you've ever wanted your analytical work to actually change how something operates — not just live in a dashboard nobody opens — this is that job.

Responsibilities

• Embed with military logistics, supply and maintenance operations to understand how decisions get made today — and where AI, automation, and better instrumentation can change the math.
• Turn operational data (logistics, maintenance, readiness, inventory) into the analyses, dashboards, and models that customer leadership actually uses to run their organizations.
• Build the data pipelines, ETL, and integrations that connect customer ERP, MES, CMMS, and logistics systems to our platform — and keep them running in restricted environments.
• Partner with our RL and platform engineers to translate operational reality into product: what the optimizer needs to know, what "good" looks like, and where our models are leaving value on the table.
• Run the quantitative work behind capacity planning, forecasting, simulation, and process redesign — and then carry the recommendations across the finish line into deployed change.
• Be the credible technical voice in front of senior military and civilian stakeholders who need to trust both you and the system.

Desired Skills

• A degree in Industrial Engineering, Systems Engineering, Operations Research, or a closely related quantitative field.
• 2+ years working on real operational problems — manufacturing, logistics, maintenance, supply chain, or similar — not just coursework or pure analytics.
• Strong Python (pandas, NumPy, the usual suspects) and SQL chops. You can move from a question to a clean answer without three meetings in between.
• Experience building dashboards people actually use (Power BI, Tableau, Grafana, or similar).
• The ability to explain a model, a tradeoff, or a recommendation to someone who has never opened a Jupyter notebook — and have them leave the room more confident, not less.
• US citizenship and the willingness to work toward a security clearance. Existing clearance is a plus, not a requirement.

Bonus Points

• Prior work in defense, government, or other regulated environments — or military service yourself.
• Cloud (AWS or Azure), APIs, ETL, and systems integration experience.
• Background in optimization, statistical modeling, simulation, or applied ML.
• Lean / Six Sigma fluency from somewhere it actually mattered.
• Comfort working in austere or air-gapped environments.

What Success Looks Like in Year One

• Customer decisions that used to run on spreadsheets and tribal knowledge are running on data you helped instrument.
• The product team is shipping features that came directly from patterns you spotted on the ground.
• Manual reporting that used to eat days of analyst time is automated and trusted.
• When senior leadership at a customer command wants to know how their logistics operation is really performing, the answer comes from a system you helped build.

Salary

The estimated salary range for this position is between $135,000  and $165,000 annually. We strive to provide a competitive salary and benefits package that aligns with our employees’ experience and qualifications. Our primary objective is to attract and retain top talent, and we firmly believe in compensating our employees fairly for their invaluable contributions.

As a rapidly expanding technology company, we extend part-ownership to all team members through an Employee Stock Option Plan. Additionally, we offer comprehensive health insurance benefits, access to the company’s 401K plan, and foster a team-oriented work environment with regular company outings!

Why Join Us

• The mission is real. Our software runs in front of people whose job is to keep the fleet moving — the consequences of getting it right are tangible.

• Small team, high leverage. You'll have visibility from the engineering trenches to the executive team, and your work will compound.

• Hard problems worth solving. Reinforcement learning applied to logistics at the scale of a military service is genuinely novel work.

• Competitive comp, meaningful equity, and the kind of professional growth that comes from being trusted with big things early.

Tagup is an equal opportunity employer and individuals seeking employment with us are considered without regard to race, color, religion, national origin, age, sex, marital status, physical or mental disability, veteran status, gender identity, sexual orientation, or any other characteristic protected by law.

Citizenship : Due to the nature of our work with the U.S. Department of Defense, applicants must be authorized to work for any employer in the U.S. We are unable to sponsor visas at this time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.