At Proposales, we’re on a mission to shape the future of business proposals, replacing static documents by defining a new online standard fully powered by web technology (literally, a piece of internet infrastructure).

Read about our mission: https://mission.proposales.com

(this page is created from scratch by Peter, Design Engineer)

We’re looking for a Lead AI Engineer to help build intelligent capabilities into the Proposales platform — including proposal generation, structured content understanding, workflow automation, and developer tooling powered by modern language models.

This role sits at the intersection of language-model powered systems, product engineering, and platform infrastructure. You will turn modern AI capabilities into reliable production systems while helping shape how our engineering team builds with AI every day.

Quick overview

• Build production-grade language-model powered systems, agents, and workflow automation

• Design infrastructure for model orchestration and asynchronous workflows in a serverless, event-driven environment

• Work closely with Product and the Core Platform team

• Stay hands-on with coding, experimentation, and system design

• Help define pragmatic practices for building and operating language-model powered features across engineering

Joining a company early is exciting — not only will you be part of defining the vision, as one of our first employees you will receive a competitive package, including a stock option program, personal training budget, and much more.

Your mission:

• Design and build reliable AI-powered product capabilities using LLMs, retrieval systems, and intelligent workflows

• Write testable, maintainable, and scalable code with a strong focus on quality and long-term maintainability

• Continuously experiment, evaluate, and iterate on AI solutions to improve performance, accuracy, and user experience

• Develop reusable AI building blocks and internal tooling that accelerate product development

• Design and maintain AI infrastructure and workflows, including orchestration, background execution, and evaluation pipelines

• Help integrate AI deeply into both product features and internal developer workflows

• Contribute to shaping our engineering culture and workflows to make Proposales a place you look forward to in the morning

How you will work with AI at Proposales:

• You will design and build language-model powered capabilities as real production systems — not isolated experiments. This includes developing MCP-based integrations, building standalone agents, and creating workflow-driven tools that solve concrete product problems.

• You will help establish service layers and architectural patterns that make agents reliable, observable, and reusable across the platform. A strong focus will be placed on pragmatic system design, ensuring AI components behave predictably within a serverless and event-driven environment.

• You will contribute to defining how AI systems are tested and evaluated, improving reliability through structured evaluation, guardrails, and iterative experimentation suited for non-deterministic systems.

• You will also help improve internal developer tooling and workflows by leveraging modern AI-assisted development practices (such as Cursor, Claude, or similar tools) while maintaining high standards for code quality and maintainability.

• The role involves working closely with infrastructure concerns such as orchestration, asynchronous execution, monitoring, and cost-awareness — treating AI as part of the platform infrastructure rather than standalone features.

• Strong architectural thinking is expected, applying software engineering principles to language-model powered systems and helping define practical patterns for model-driven infrastructure within a serverless ecosystem.

What we believe in:

We use a serverless, continuous-delivery infrastructure hosted on Vercel, built using Next.js and written in TypeScript.

We treat AI as an engineering discipline — reliability, observability, evaluation, and thoughtful user experience matter as much as model capability.

We stay pragmatic when working with AI — we explore and adopt external vendors and tools when they provide clear value, while designing our systems so we can evolve and adapt as the ecosystem changes.

AI at Proposales is treated as infrastructure as much as product — including workflows, orchestration, evaluation, and automation powered by tools like Trigger.dev.

When deciding on a tech stack for a new sub-project, we usually take the opportunity to assess new tech early and plan for long-term benefits and maintainability over short-term goals. But we also value simple solutions over smart ones, and embrace test-driven development and pair programming, favoring higher code quality over faster development times.

We generally prefer a functional programming style over object-orientation and like to avoid abstractions like middlewares or ORMs.

We prefer monorepos with multiple smaller projects, instead of one monolithic application. We avoid code duplication by extracting core logic and UI into separate internal libraries.

We use AI where it clearly helps — in product and internal tooling — while keeping automation and human judgment in the right balance.

Core AI skills and technologies:

LLMs (large and small language models)

Deep learning and NLP systems

RAG architectures and retrieval systems

AI infrastructure and evaluation tooling

Agent frameworks and standalone AI agents

Trigger.dev (background jobs & AI workflow orchestration)

MCP (Model Context Protocol)

Vector databases and semantic search

Prompting, evaluation, and experimentation workflows

Some of the technologies you would be working with:

Python

TypeScript / JavaScript

Next.js

Node.js

PostgreSQL

Vercel

Vercel AI SDK

Serverless architectures

OpenAI / Anthropic or similar model providers

Embedding models and vector stores

Event-driven and workflow orchestration systems

A bit about you:

• Strong coding ability in Python and/or JavaScript / TypeScript

• Solid understanding of deep learning fundamentals, large and small language models, and Natural Language Processing (NLP) concepts

• Experience building production-grade AI or LLM-powered applications

• Understanding of RAG systems, prompting strategies, and evaluation concepts

• Experience designing APIs and backend systems for product development

• Experience or strong interest in AI infrastructure, workflow orchestration, or distributed AI systems (e.g. Trigger.dev, background jobs, agents, or similar systems)

• Experience helping teams adopt new technologies or engineering practices

• You are pragmatic about AI — balancing experimentation with reliability and real user value

• You are great to collaborate with and enjoy working closely with product and design

• You believe in code quality through code reviews, pair programming, and test-driven development

• You believe in self-management and clear communication over heavy processes

• Willingness to learn new technologies and move between different tech stacks as AI evolves rapidly

• Familiarity with secure development practices and awareness of compliance-oriented environments (e.g., handling sensitive data, auditability, or regulated systems)

• Working proficiency and communication skills in verbal and written English

• You live in Stockholm and thrive in an office-first team culture