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