Applied AI Engineer (Squad Lead)

🚀 Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies across a wide range of industries.

🧠 About the Product:

We’re hiring for a global technology-driven financial services platform serving millions of users across multiple regions and offering access to multi-asset trading, including stocks, indices, currencies, and digital assets.

The product operates as a regulated, data-intensive financial ecosystem, processing massive volumes of transactions and real-time customer interactions every day.

The company is well-funded, profitable, and known for pushing innovation in AI, automation, and data governance across its operations.

🤖 About the Role:

We’re looking for an Applied AI Engineer (Squad Lead) to join a fast-paced, AI-first environment where AI is already a core part of how the company operates.

This is not a role focused on adding isolated AI features or building prototypes that never reach production. You’ll take real business challenges and turn them into production-grade AI agents and applications — end to end, from idea and POC to deployment and continuous improvement.

You’ll have significant autonomy and ownership, work with modern GenAI and agentic technologies, and use AI-native development workflows every day.

As the squad grows, you’ll also guide other engineers while remaining deeply hands-on.

🔧 What you’ll do:

Design, build, and deploy AI-powered agents and applications from concept through production

Develop and maintain AI pipelines for data ingestion, embeddings, retrieval, and LLM orchestration

Write high-quality backend and frontend code to embed AI into user-facing tools and internal platforms

Build APIs and integrations with CRMs, databases, and third-party services

Work with structured, unstructured, and vectorized data to power intelligent workflows and decision-making

Monitor, evaluate, and continuously improve AI systems for performance, reliability, and cost efficiency

Design and implement scalable, secure, and observable cloud-based solutions

Own production systems end-to-end, including debugging, enhancements, and ongoing optimization

Collaborate closely with product and business stakeholders to translate real-world requirements into high-impact AI solutions

Guide other engineers and help shape the technical direction of the squad while staying hands-on

🛠️ Tech stack:

AI: LLMs, RAG, AI Agents, Multi-Agent Systems, Tool Calling, Structured Outputs, Memory

AI Frameworks: LangChain, LangGraph, LangSmith, Semantic Kernel

AI Development: Cursor, Claude Code, AI-native development workflows

Data: Vector Databases, Embeddings, Structured & Unstructured Data

Backend: APIs, Integrations, Modern Backend Technologies

Frontend: Modern frontend frameworks for complex AI-powered workflows

Cloud: Azure / AWS / GCP

Architecture: Distributed Systems, Event-Driven Architectures, Observability, Security

✅ What we’re looking for:

5+ years of software engineering experience in backend or full-stack development

Proven experience using AI-native development workflows such as Cursor or Claude Code on a daily basis for production systems

Hands-on experience building production AI agents, including RAG, multi-agent orchestration, tool calling, structured outputs/validation, memory, and workflow management

Proven track record of deploying LLM-powered systems into production

Strong backend and modern frontend development skills for building complex workflows

Experience with Azure, AWS, or GCP and designing scalable cloud architectures

Practical experience with vector databases and embedding pipelines

Deep understanding of system design, scalability, observability, and security

Experience leading small development teams or owning a technical domain

Strong communication, stakeholder management, and problem-solving skills

Fluent English — written and verbal

⭐️ Nice to have:

Experience with LangChain, LangGraph, LangSmith, Semantic Kernel, or equivalent GenAI frameworks

Experience building AI systems in regulated or compliance-driven environments

Background working with internal business platforms such as customer service, retention, operations, or compliance

Strong understanding of business process automation and operational intelligence

Familiarity with event-driven architectures and distributed systems

Experience implementing AI evaluation frameworks and automated testing for LLM-based systems

💡 Why this role is interesting:

AI-first environment: AI is already a core part of the company’s operations, not an experimental side project

Production impact: build and deploy AI agents that solve real business problems and are used in production

End-to-end ownership: take solutions from idea and POC through deployment, monitoring, and continuous improvement

Modern GenAI: work hands-on with LLMs, RAG, agents, multi-agent orchestration, tool calling, and vector databases

AI-native development: use tools like Cursor and Claude Code as part of your daily engineering workflow

Technical leadership: lead and mentor other engineers while remaining hands-on with architecture and development

Real scale: build secure, observable, cloud-based solutions for a global financial platform serving millions of users

Business impact: work directly with stakeholders to turn complex operational challenges into scalable AI solutions

🎁 What we offer:

20 days of vacation leave per calendar year + official national holidays of the country you are based in

Full accounting and legal support in all countries we operate

Fully remote work model

Powerful workstation for your work

Co-working space when you need it

Highly competitive compensation package

Yearly performance and compensation reviews