Backend Engineer — High-Volume Data Processing

Location: Dumbo, Brooklyn, NY
Work Arrangement: Onsite, 5 days per week (required)
Employment Type: Full-time
Base Salary: $220,000–$300,000
Equity: Competitive equity package
Visa: Open to OPT and H-1B transfers; additional sponsorship may be considered
Relocation: Up to $10,000 in relocation assistance

About the Opportunity

A rapidly growing AI and data company is building the data infrastructure that powers next-generation AI models. The company works with proprietary enterprise data, transforming information generated through real-world business operations into de-identified datasets for leading AI research organizations.

Having grown from $0 to a multi-eight-figure annualized run rate within months, the business is scaling rapidly with a lean engineering team of approximately five people.

This is an opportunity to join at an early stage, take meaningful ownership of mission-critical systems, and directly influence the architecture and reliability of a high-impact data-processing platform.

The team is seeking a Backend Engineer to build and evolve the systems that transform sensitive enterprise information into high-quality, AI-training-ready datasets.

The core focus is on the processing logic applied to the data itself , rather than traditional data engineering, ETL, or infrastructure work centered primarily on moving data between systems.

What You#39;ll Do

• Design, build, and scale multi-stage, high-volume data-processing pipelines that de-identify sensitive enterprise data from collaboration tools, email, cloud storage, code repositories, and project-management systems.
• Own backend systems end-to-end, from architecture and implementation through debugging, correctness validation, production monitoring, and recovery.
• Develop safeguards to detect silent failures, duplicate outputs, stale data, and other data-quality issues before customer delivery.
• Build reliable mechanisms for retries, checkpoints, partial failures, replay, backfills, and rollbacks across asynchronous workflows, batch workers, queues, and object storage.
• Develop internal tools and dashboards to monitor pipeline performance, investigate data quality, and inform release decisions.
• Partner with ML, full-stack, platform, and security engineers to support new data modalities and expand processing capabilities.
• Improve the reliability, observability, and scalability of systems handling complex and sensitive datasets.

What We#39;re Looking For

Required Qualifications

• 3–10 years of software engineering experience , with direct ownership of production backend systems.
• Demonstrated experience shipping and operating production software, ideally involving multi-stage, high-volume data-processing pipelines.
• Relevant undergraduate STEM degree from a top-30 U.S. institution.
• Strong understanding of distributed and asynchronous backend systems, including:
• Queues, workers, and concurrency
• Idempotency and retry strategies
• Partial failures and fault tolerance
• Recovery, replay, and data consistency
• Meaningful full-time experience at an early-stage or high-growth startup, with demonstrated ownership, adaptability, and comfort operating in ambiguous environments.
• Strong proficiency in a general-purpose backend programming language.
• Ability and willingness to work onsite five days per week in Dumbo, Brooklyn, NY.

Important: The undergraduate education requirement and five-day onsite requirement are firm. Candidates who do not meet both criteria will not be considered.

Technical Environment

The current technology stack includes:

Python, AWS, Airflow, AWS Batch, SQS, S3, DynamoDB, and PostgreSQL

Python experience is not mandatory. Strong backend engineers with experience in Go, Rust, Java, or other general-purpose languages are encouraged to apply.

Particularly relevant technical experience includes:

• AWS and cloud-based backend systems
• Batch processing and workflow orchestration
• Natural Language Processing (NLP) and Named Entity Recognition (NER)
• Distributed systems and asynchronous processing
• Data quality, correctness, and production reliability
• Internal tooling, monitoring, and observability

The team values engineers who think beyond implementation. Ideal candidates enjoy understanding how data-processing systems behave, building tools to investigate performance and quality, diagnosing complex failures, and solving problems across the entire workflow.

A backend-focused engineer with some full-stack experience can also be a strong fit.

Experience That Stands Out

Candidates may be particularly well suited to this role if they bring:

• Experience at a highly regarded engineering organization combined with meaningful startup experience.
• A clear record of career progression and increasing technical ownership.
• Hands-on AWS experience.
• Experience building or operating batch-processing pipelines and workflow orchestration systems.
• Experience developing internal tools, dashboards, or observability systems for data-processing workflows.
• A strong understanding of production failure modes, data correctness, recovery strategies, and system reliability.
• The ability to take a broad, ambiguous problem and deliver a reliable end-to-end solution.

Who May Not Be a Fit

This position is less suited to candidates whose experience is primarily focused on:

• Traditional data engineering, data platforms, or infrastructure work centered on moving data between systems.
• ETL development using tools such as Databricks, without substantial ownership of the underlying processing logic.
• Frontend-heavy full-stack development without significant backend engineering depth.
• Large-company engineering environments without meaningful early-stage or high-growth startup experience, unless the candidate#39;s technical background is directly relevant.
• Startup exposure limited mainly to internships or short-term engagements.

Team amp; Culture

You#39;ll join a small, high-performing engineering team operating in a fast-moving environment with significant customer demand and substantial room to influence the product and technical direction.

The team emphasizes:

• First-principles problem-solving: Understand the underlying challenge and build the right solution.
• Ownership and accountability: Take responsibility for systems and outcomes from start to finish.
• Bias toward action: Move quickly, experiment, and learn through execution.
• Engineering excellence: Deliver reliable, high-quality work that meets a high technical bar.
• Humility and collaboration: Support teammates, share knowledge, and work together toward common goals.
• Outcome-driven execution: Prioritize meaningful results over activity or output alone.

With a very small engineering team, this role offers significant responsibility, close collaboration, and the opportunity to help shape critical systems as the business scales.

Compensation amp; Benefits

• Base Salary: $220,000–$300,000
• Equity: Competitive equity package
• Medical, Dental amp; Vision: 100% covered
• Paid Time Off: Unlimited PTO
• Relocation Assistance: Up to $10,000

Visa amp; Relocation Support

The company is open to visa transfers, including OPT and H-1B transfers .

Additional visa sponsorship may be considered for exceptional candidates, depending on individual circumstances. Sponsorship is not guaranteed and will be evaluated on a case-by-case basis.

Candidates relocating to New York may be eligible for up to $10,000 in relocation assistance.

Interview Process

The following stages begin after a candidate has been submitted to the hiring team. Agency screening and the initial resume review are not counted as interview stages.

Stage 1 — Introductory Call (30 minutes)

A conversation with the hiring manager covering your background, motivations, experience, and alignment with the role.

Stage 2 — System Design (1 hour)

A distributed-systems and data-processing exercise focused on architecture, technical tradeoffs, scalability, and correctness in high-volume backend pipelines.

Stage 3 — Take-Home Technical Assessment (A few hours)

An independent, practical backend coding exercise evaluating engineering fundamentals and hands-on problem-solving. The engineering team will review the completed submission.

Stage 4 — Final Onsite Interviews (2 hours)

An onsite session at the Dumbo, Brooklyn office with engineering and leadership. The final round evaluates technical depth, problem-solving, and team fit while giving candidates an opportunity to meet the team and learn more about the business.

Travel Support: Candidates who are not currently based in New York will be flown in and provided with accommodation for the final onsite interview.