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New Grad Engineer Jobs in Mahwah, NJ (NOW HIRING)

Maximor AI

Software Engineer (New Grad)

New York, NY · On-site

... New grad" is how you start here. It isn't a track, and it isn't a ceiling. Problems Worth Your ... Context engineering over transactions, ledgers, contracts, policies, and historical decisions ...

Confido

New Grad Software Engineer

New York, NY · On-site

$170K/yr

The Role As a Full-Stack Engineer (Early Career) at Confido, you will help build new product features and systems from the ground up. You'll work closely with experienced engineers to develop AI ...

Whatnot

Software Engineer, 2027 New Grad

New York, NY · On-site

$155K - $160K/yr

The people here are shaping how an entirely new industry develops. As a remote co-located team, w ... The engineering team operates with a high level of autonomy so we need to hire people we can trust.

N1

New Grad Software Engineer (Backend Rust)

New York, NY · On-site +1

$120K - $260K/yr

As a key member of the software engineering team, you will spearhead the development of the core ... The range displayed on each job posting reflects the minimum and typical maximum target for new ...

Uniswap Labs

Software Engineer - Early Career

New York, NY · On-site

$138K - $200K/yr

We're hiring our first new-grad engineering cohort. Almost nobody in crypto hires and develops early-career engineers in a structured way - we're going to. You'll join one of our engineering pods ...

N1

New Grad Software Engineer (Full Stack)

New York, NY · On-site

$100K - $180K/yr

We are seeking a Software Engineer, Full-Stack to join our engineering team full-time. This role ... The range displayed on each job posting reflects the minimum and typical maximum target for new ...

Uncountable

Product Manager (New Grad)

New York, NY · On-site

$125K - $140K/yr

Thank you for your interest in Uncountable Engineering! Description Uncountable is looking for a ... This role is an in-person role working out of either our San Francisco or New York office. Primary ...

Flexport

Area Manager - New Grad

Newark, NJ

... Engineering teams. You Should Have * A bachelor's degree completed within the last 12 months, or ... Strong problem-solving skills and comfort learning new processes quickly in a fast-paced, sometimes ...

Maximor AI

Startup Generalist (New Grad)

New York, NY · On-site

The accountant + engineer loop is the moat. The people who sit with controllers and build from what ... In-person in New York City. Five days a week, in the same room as the founders. That's the point of ...

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All JobsNew Grad Engineer JobsNew Grad Engineer Jobs in Mahwah, NJ

New Grad Engineer information

See Mahwah, NJ salary details

$11K

$72.9K

$126K

How much do new grad engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for new grad engineer in Mahwah, NJ is $72,856.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,200.00 and $83,300.00 per year, depending on experience, location, and employer.

What is a new grad engineer?

A New Grad Engineer is an individual who has recently graduated from a university or college with an engineering degree and is starting their professional career. These engineers are typically in entry-level positions, where they apply the knowledge and skills acquired during their studies to real-world engineering problems. New Grad Engineers often participate in training programs, work under the guidance of more experienced engineers, and gradually take on more responsibility as they gain experience. Their roles can vary widely depending on the industry and the specific company they join.

What are the key skills and qualifications needed to thrive as a new grad engineer?

To thrive as a New Grad Engineer, you generally need a solid foundation in engineering principles, problem-solving abilities, and a relevant bachelor's degree. Familiarity with industry-standard software, such as CAD tools or programming languages, and internships or relevant project experience are highly valued. Strong communication, teamwork, and a willingness to learn help new engineers adapt quickly and collaborate effectively. These skills enable new engineers to contribute meaningfully to projects, integrate into teams, and grow within fast-paced technical environments.

What types of projects are new grad engineers typically assigned during their first year?

As a new grad engineer, you can expect to start with smaller, well-defined tasks that allow you to become familiar with the company's tools, processes, and codebase (if applicable). These projects are often part of a larger team effort and are designed to help you build confidence while contributing meaningfully. Over time, you'll likely be given more complex assignments and may have the opportunity to take ownership of specific features or problem areas. Regular collaboration with senior engineers and cross-functional teams is common, providing valuable learning and mentorship opportunities as you develop your skills.

What is the difference between New Grad Engineer vs Entry Level Engineer?

AspectNew Grad EngineerEntry Level Engineer
Required CredentialsBachelor's degree in engineering or related fieldBachelor's degree in engineering or related field
Work EnvironmentInternship or first full-time role, often in training programsFull-time position, performing basic engineering tasks
Employer & Industry UsageCommonly used for recent graduates entering engineering rolesUsed for professionals with minimal work experience in engineering

Both roles typically require a bachelor's degree in engineering. A New Grad Engineer often refers to someone just starting their career, possibly in a structured training program, while an Entry Level Engineer is a full-time employee performing foundational engineering tasks. The terms are frequently used interchangeably, but 'New Grad Engineer' emphasizes recent graduation, whereas 'Entry Level Engineer' highlights minimal experience.

Are new graduate engineers struggling to find jobs?

New graduate engineers often face competitive job markets, but opportunities are available for those with strong technical skills, relevant internships, and certifications. Success depends on networking, interview preparation, and staying updated with industry tools and trends.

How to get a job as a new graduate engineer?

To secure a job as a new graduate engineer, candidates should focus on building a strong technical foundation through relevant coursework and internships, develop proficiency in engineering tools and software, and prepare a professional resume highlighting project experience. Networking with industry professionals and applying to entry-level positions through company career portals or job boards are also essential steps.

What jobs do new graduate engineers go into?

New graduate engineers typically start in entry-level roles such as design engineer, manufacturing engineer, quality engineer, or systems engineer. These positions often require knowledge of engineering principles, technical skills, and sometimes certifications or internships to qualify for the roles.

What cities near Mahwah, NJ are hiring for New Grad Engineer jobs?

Cities near Mahwah, NJ with the most New Grad Engineer job openings:

New Grad Engineer jobs near you

Software Engineer (New Grad)

Maximor AI

New York, NY • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 12 days ago

Key responsibilities

  • Own the development of AI agents that connect to and automate finance systems such as ERPs, banks, billing, payroll, CRM, contracts, spreadsheets, email, and Slack.

  • Build and improve systems for verifying, guardrails, observability, and evaluation of non-deterministic AI to ensure trustworthiness in finance workflows.

  • Ingest, normalize, and reconcile data from various enterprise systems to create a unified source of financial truth.

Job description

About Maximor
Most AI companies are building copilots.
Maximor is building the AI operating system for the CFO office. Our Audit-Ready AI Agents connect to a company's existing finance stack-ERPs, banks, billing, payroll, CRM, contracts, spreadsheets, email, and Slack-and automate the work behind the entire order-to-cash process, record-to-report process, treasury management, financial reporting, and audit readiness.
The goal isn't to help the finance team write better prompts.
The goal is for finance teams to review exceptions while AI does the rest.
What makes Maximor different is our Unified Finance Context-a financial understanding layer that captures transactions, policies, contracts, historical decisions, and accounting judgment. On top of it sit Audit-Ready AI Agents that can reason, explain their decisions, escalate uncertainty, and continuously improve.
We've raised $9M led by Foundation Capital, alongside BoldCap, Gaia Ventures, Aravind Srinivas (CEO of Perplexity), and finance leaders from Zuora, Ramp, Gusto, MongoDB, Zoom, and the Big Four.
What You'll Own
You won't get a starter ticket and a six-month ramp plan.
You'll join a pod of 2-3 engineers that owns a finance domain end-to-end-revenue, cash, close, reporting, payroll, fixed assets, tax, or controls-and you'll own real surface area inside it from your first month: context, prompts, tools, evals, guardrails, and the product around them. A senior engineer pairs with you closely at the start. The bar is that you're scoping and shipping your own work by the end of your first quarter.
No PM writes your specs. No architecture committee approves your ideas. You'll sit with the controllers, accountants, and CFOs who do the work today, understand it properly, then build the agent system that replaces it.
"New grad" is how you start here. It isn't a track, and it isn't a ceiling.
Problems Worth Your Brain
  • How do you build AI agents that finance teams and auditors can trust? Verification, guardrails, observability, and evaluation systems for non-deterministic AI.
  • How do you give an agent the right financial context? Context engineering over transactions, ledgers, contracts, policies, and historical decisions-without bloat, drift, or data leakage.
  • How do you turn messy enterprise systems into a unified source of truth? Ingest, normalize, and reconcile data from ERPs, banks, payroll, billing platforms, CRMs, and email.
  • How do you build agents that get better over time? Systems that explain their reasoning, escalate uncertainty instead of guessing, and improve measurably from human corrections.
  • How do you orchestrate durable AI workflows in the real world? Long-running, replay-safe workflows across flaky, stateful enterprise systems.
  • How do you safely write back to systems of record? Idempotent, audit-ready updates to ERPs and financial systems with full traceability.
A Few Strong Opinions
  • The engineer who can't operate AI agents fluently is becoming obsolete, fast. Fluency with Claude Code, Cursor, and internal agent tooling is a second cortex. Come knowing how to use them; leave knowing how to build with them.
  • "Backend vs. frontend" is dissolving. The agents do the typing. The constraint is product judgment, system design, and the ability to close the loop from problem to shipped feature. Our engineers ship full-stack when the work calls for it.
  • The pod is the unit of leverage. Two engineers who can hold an entire module in their heads ship more than ten engineers who each own a slice. Specialization across pods, generalist within them.
  • The accountant + engineer loop is the moat. Engineers who sit with controllers and build from what they see compound faster than the ones who don't. That starts on day one, not after you've "earned" customer access.
  • We hire for slope as much as intercept-but the intercept still has to clear the bar. We care how fast you learn. We also care that you've already built things that were hard.

What Great Looks Like Here
  • You learn fast and ship faster. You can pick up an unfamiliar codebase or an unfamiliar domain and be productive in days, not weeks. The ability to understand a finance workflow and translate it into software is the single most important skill on this team.
  • You think like an owner. You're a current or future founder who scopes your own work, thinks from the customer's perspective, owns decisions, and drives outcomes without waiting for direction.
  • You solve problems end to end. The team is split vertically. Every engineer makes decisions across the LLM pipeline, infrastructure, backend, and UX.
  • You care about getting it right. A 100% solution beats an 80% one. When something breaks, you dig until you understand why-not just until it stops erroring.
  • You operate AI at two levels. You use coding agents fluently to ship faster, and you have real craft in building the agents that are the product: prompt and context design, tool use, evals, and knowing when a model is the right tool and when plain code is.
  • You communicate clearly. You ask good questions, share progress without being asked, and say "I'm stuck" early instead of late.

What You Should Have Done Before
  • Finishing a bachelor's or master's degree, or graduated within the past year. Computer science, machine learning, or AI strongly preferred; adjacent quantitative degrees welcome if the work backs it up.
  • At least one substantial software engineering or AI engineering internship. Early-stage and AI-native startups count for more here-if you've shipped to production at a company under 50 people, tell us about it.
  • Hands-on experience building with AI agents. Internship, research, coursework, or a serious side project all count. We care that you've actually built one, watched it fail in an interesting way, and can explain what you changed.
  • Real fluency with coding agents. Claude Code, Cursor, or equivalent. You have opinions about which to reach for and when, and you've shipped production code through them.
  • Strong fundamentals in a modern language. Our stack is Python. If your depth is in C++, Java, Go, or Rust, strong fundamentals matter more-be ready to ramp fast.
  • Something real you can walk us through in depth. A side project, a research prototype, an open-source contribution, a hackathon build. We'll go deep on it, so pick something you actually understand.

You'll Stand Out If
  • You've done research in AI, ML, or systems-published or in progress at NeurIPS, ICML, ICLR, ACL, or similar. We weight real-world impact over citation count.
  • You've TA'd or course-assisted a serious systems, ML, or compilers course. Teaching a hard thing well is a strong signal.
  • You've shipped a side project that real people actually used-not just starred.
  • You've contributed to open source that other people depend on.
  • You've built evals, verification, or observability for something non-deterministic and watched it catch a bug before a human did.
  • You've interned at a pre-seed through Series B startup and thrived in the ambiguity.
  • You've done well in competitive programming or olympiads-ICPC, IMO, IPhO, Putnam, or similar.
  • You're curious about fintech, accounting, or how money actually moves.
The Upside
  • Exceptional teammates with high ownership and direct access to customers, CFOs, controllers, and founders.
  • Competitive pay and meaningful early-stage equity.
  • Full medical, dental, and vision coverage for employees and dependents, plus 401(k) match.
  • Meals, a stocked NYC office, and the chance to help define an entirely new category: Audit-Ready AI for Finance.

The Details
  • In-person in New York City. We build in the same room, on purpose.
  • Visa status isn't a filter here. We support OPT and we go the distance on longer-term status for the engineers we hire. The paperwork is our problem, not yours.

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