Founder AI ML Engineer

This is a founding AI / ML engineer role at Ultra-Ops.

Ultra-Ops is human managed, AI-powered for construction, delivering:
Blueprint Takeoffs Service Dispatch AI Sales Automation Marketing Billing Analytics

Ultra-Ops operates today as an existing construction operations company, providing human-delivered services to real construction businesses. The company is now rapidly transitioning those proven human workflows into AI-augmented and AI-automated systems.

This role is not research-only and not experimental. You will be building production AI systems inside a live business with existing customers, active revenue, and ongoing discussions with angel investors and VCs. Speed of execution matters.

As a founding engineer, you will work directly with the founder to:

• Define the AI roadmap and technical architecture

• Decide what to build vs. buy

• Translate operational pain points into deployable AI systems

• Move quickly from prototype to production

You will have meaningful influence over:

• Model and tooling selection

• Data strategy and pipelines

• System architecture and integrations

• Future AI hiring and team direction

This is a builder role for someone who wants ownership, autonomy, and a direct hand in shaping both the product and the company. There are two technical people in the company - this is a phenomenal time to be the third.

Read the founder's entire resume on Linkedin - he used to report to Arjun Malhotra, co-founder of HCL

Requirements

The primary responsibility is to design and implement AI modules for construction operations, starting with the following focus areas.

Blueprint Ingestion & Understanding:

• Build systems to ingest construction blueprints and plan sets (PDFs)

• Apply OCR and document parsing to extract structured data

• Support layout understanding, annotations, and metadata extraction

• Produce outputs usable by downstream systems (CRM, proposals, takeoffs)

Employee Productivity & Internal AI Tools:

• Develop AI tools that assist individual employees with email drafting, summarization, and response generation

• Ground outputs in CRM data, operational history, and internal knowledge

• Integrate AI assistance directly into daily workflows

Product Manuals & Technical Intelligence:

• Build AI systems that ingest product manuals, spec sheets, and technical documentation

• Enable accurate question-answering and knowledge retrieval

• Support outputs for internal tools, websites, webpages, and customer-facing chatbots

• Implement retrieval-augmented generation (RAG) or equivalent architectures

Core Technical Skills:

• Strong Python experience

• Hands-on experience with modern ML / AI frameworks (e.g., PyTorch, transformers)

• Experience with OCR, NLP, or document-processing pipelines

• Familiarity with LLMs, embeddings, vector databases, and RAG systems

• Ability to design APIs and integrate AI into production systems

Engineering Mindset:

• Comfortable working with real-world, imperfect data

• Ability to move from prototype to production quickly

• Experience integrating AI into existing software stacks

• Understanding of iteration, monitoring, and improvement in live systems

Nice to Have:

• Experience with construction, AEC, or blueprint data

• Front-end or product integration experience

• Exposure to MLOps or model deployment

• Interest in mentoring junior engineers as the team grows

Founder Expectations:

• Comfort operating with ambiguity

• Bias toward execution and delivery

• Willingness to prioritize speed over polish

• Desire to build a company, not just a codebase

This is a founding technical role for someone who wants to build real AI systems that replace and enhance human workflows in construction operations, inside a company with customers, revenue, and investor momentum already underway.