Founding Software Engineer - AI & Operations (Full-Stack)

Wallingford, CT, US Mid Level AI Software Engineer

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Skills & Technologies

AnthropicClaudeOpenai

About This Role

AI job market dashboard showing open roles by category

The short version

We make precast concrete — the stuff underneath roads, buildings, and utilities across the Northeast. Our plants run on spreadsheets, memory, and paper. We're hiring one engineer to change that, with full ownership of architecture, stack, and roadmap.

You won't inherit legacy code. You won't ship features into a backlog nobody reads. You'll build systems that people 50 feet from your desk use every day — and they'll tell you, immediately and honestly, whether they work.

Why this role is different* You choose the stack. Green\-field. Data model to UI, it's yours.

  • AI is the job, not a bolt\-on. Real problems waiting for it:
  • + We recently caught a $6,000 forklift parts invoice that a 5\-minute manual price check found for half the cost. We want an OCR \+ LLM pipeline that catches every one of those automatically.

+ We have 10\+ years of sales history and no forecasting. Every busy season, high\-demand products stock out. You'll build the model that flags shortfalls before they happen.

+ A heater once ran all winter and nobody noticed until the bill review — years later. You'll build anomaly detection on energy and utility data so that never happens again.

*

  • Direct P\&L impact. Your code will save real money, measurably, within months — not "improve engagement metrics."
  • You'll work across the whole business: production scheduling, dispatch and truck routing (including oversized loads), job cost accounting, predictive maintenance, procurement, and compliance.

What you'll build (first 12–18 months)* AI invoice auditing — OCR \+ LLM pipeline that extracts line items from scanned vendor invoices and checks them against market pricing, with human review where errors are costly

  • Demand forecasting — ML/time\-series models on a decade of sales data, cross\-referenced with mold inventory, to recommend what to pour next
  • Unified inventory \& job costing — one system for raw materials, finished goods, labor hours, and purchases tied to specific jobs
  • Route \& load planning — truck routing by weight capacity, trailer selection for over\-weight/over\-width loads, freight costs flowing into job cost sheets
  • Predictive maintenance — evaluate our existing MaintainX deployment (keep it, replace it, or integrate it — your call), then use maintenance history to flag high\-wear parts before they fail
  • Compliance \& alerts — fleet registrations, insurance, inspections, and real\-time shipping/receiving notifications

Logistics* Location: 173 Church Street, Yalesville, CT — onsite with the people you're building for *(adjust if hybrid flexibility is approved)*

  • Compensation: \[$X–$Y base] \+ \[benefits summary] *(strongly recommend posting a range — it materially improves reply and apply rates)*
  • Process: intro call technical deep\-dive on a system you built short practical exercise (invoice\-extraction design) meet the plant team offer. Two weeks, start to finish, if you move fast.

Requirements

  • 3\+ years of professional engineering experience, including at least one production system you owned end\-to\-end (data model API UI)
  • Strong full\-stack fundamentals: a modern backend language, solid SQL/relational design, and a modern frontend framework — we care more about judgment than any specific stack
  • You've shipped LLM API integrations into production (OpenAI, Anthropic, etc.) — structured, task\-specific automation, not chatbot demos
  • You've worked with OCR / document extraction and turned messy scans into clean, queryable data
  • You know when a simple regression beats a fancy model — and when AI doesn't earn its complexity
  • You use AI coding assistants (Claude Code, Copilot) daily and ship faster because of it
  • You genuinely enjoy sitting down with a dispatcher or plant manager, understanding their manual process, and turning it into software they actually adopt
  • You're self\-directed and comfortable being the first engineer

Bonus points: manufacturing/logistics/construction software, route optimization or constraint problems, anomaly detection on time\-series data, AI\-assisted procurement tools.

You're probably *not* a fit if* You want a large engineering org, a defined career ladder, and someone else deciding the architecture

  • You need a product manager between you and your users
  • You're only interested in fully remote work

Benefits

  • Paid Vacation
  • Paid Holidays and Sick Time
  • Company 401K 10% Match
  • Group Medical and Dental

Role Details

Title Founding Software Engineer - AI & Operations (Full-Stack)
Location Wallingford, CT, US
Category AI Software Engineer
Experience Mid Level
Salary Not disclosed
Remote No

About This Role

AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.

The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.

Across the 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At United Concrete Products, this role fits into their broader AI and engineering organization.

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

What the Work Looks Like

A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

Skills Required

Anthropic (6% of roles) Claude (12% of roles) Openai (10% of roles)

Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.

Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.

Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.

Compensation Benchmarks

AI Software Engineer roles pay a median of $218,500 based on 729 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400.

Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.

United Concrete Products AI Hiring

United Concrete Products has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Wallingford, CT, US.

Location Context

Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).

Career Path

Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.

From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.

If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.

What to Expect in Interviews

Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.

When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.

AI Hiring Overview

The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.

The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

The AI Job Market Today

The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.

The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.

AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.

Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.

The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.

Frequently Asked Questions

Based on 729 roles with disclosed compensation, the median salary for AI Software Engineer positions is $218,500. Actual compensation varies by seniority, location, and company stage.
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
About 15% of the 4,317 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
United Concrete Products is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Software Engineer positions include Staff Engineer, AI Architect, Engineering Manager. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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