Software Engineer - Applied AI / Product Engineering
MLabs
- Standort
- New York, New York, United States
- Veröffentlicht
- 20. Okt. 2026
Prüfe vor der Bewerbung auf der Website des Arbeitgebers, ob die Stelle noch offen ist und welche Bedingungen gelten.
Stellenbeschreibung
Die Oberfläche ist auf Deutsch. Die Titel und Beschreibungen der Arbeitgeber bleiben in ihrer ursprünglichen Veröffentlichungssprache, die Englisch sein kann.
Location: New York, United States (Office) - NYC - SoHo Office
On-Site | Full-time
Compensation: $160K - $250K
We are hiring on behalf of our client, a high-growth, Series A-backed artificial intelligence company operating in the commercial real estate (CRE) sector who is seeking an experienced Software Engineer – Applied AI / Product Engineering to join its engineering team in New York City.
Our client delivers an enterprise-grade AI platform that automates complex commercial real estate workflows, integrating email, financial models, presentation decks, and property databases into a unified, intelligent system. Having already secured enterprise multi-year contracts with top global commercial brokerages, the organization is scaling rapidly to meet significant market demand.
This role focuses on designing, building, and deploying AI-driven products and agentic systems. The ideal candidate thrives in a fast-paced environment, takes full end-to-end ownership of features, and continuously explores evolving AI paradigms to build robust, practical solutions for enterprise users.
Key Responsibilities
Product & AI Engineering: Design, build, and deploy agent-centric software architectures and end-to-end AI workflows beyond basic conversational interfaces.
End-to-End Feature Ownership: Manage the full product development lifecycle—from sitting directly with end-users to understand core pain points, through architectural design, implementation, and deployment.
Agent Evaluation & Harnessing: Develop, maintain, and defend robust evaluation frameworks, harness selections, and context management strategies (context window optimization, filtering, and retrieval).
Domain Knowledge Extraction: Collaborate directly with industry domain experts to distill complex workflow logic into structured system requirements, prompts, and evaluation metrics.
Continuous Paradigm Evaluation: Actively benchmark, test, and re-evaluate emerging LLM models, frameworks, and agent paradigms to continuously refine and improve system performance.
Proven AI Engineering Experience: Demonstrated track record of shipping production-level software with autonomous LLM agents or workflows at its core.
Full-Stack / Product Mindset: Ability to own features end-to-end without relying on static product specs or partial hand-offs.
Technical Rigor & System Design: Ability to defend technical design choices around context management, system evaluation, framework choices, and agent harnesses.
Strong AI Curiosity: Proactive approach to testing new models, agentic frameworks, and AI tools as they are released.
Fast Learning & Domain Synthesis: Capability to rapidly absorb complex domain expertise (e.g., financial underwriting or commercial real estate logic) and translate it into technical specifications.
On-Site Availability: Ability to work full-time on-site, five days a week, at the SoHo, NYC office.
Competitive base salary and equity packages reflecting early-stage growth.
Comprehensive health, dental, and vision insurance options.
Opportunity to work directly alongside founding leadership in a high-density, collaborative environment.
Direct involvement in defining product architecture for enterprise AI applications.
Interview Process
Initial Recruiter Screening: Conversation to discuss experience, background, and alignment with the role.
Technical Deep-Dive / System Design: Technical discussion focusing on past AI project execution, agent architecture, and system evaluation design choices.
On-Site / Product Execution Session: Practical problem-solving and domain synthesis exercise with the core engineering team.
Final Leadership Interview: Alignment on team vision, culture, and final offer details.
Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search.
Commitment to Equality and Accessibility:
At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing human-resources@mlabs.city.
MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd’s Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting legal@mlabs.city.