Applied AI Engineer (Squad Lead)

Adaptiq is a technology hub specializing in building R&D teams for high-end product companies. The product is a hyper-scale fintech platform serving over 40 million users. The role involves building production-grade AI agents and applications using modern GenAI technologies, from concept to deployment.

• 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 internal systems (CRM, databases, third-party services) for seamless automation and data flow.
• Work with structured, unstructured, and vectorized data to support intelligent workflows and decision-making.
• Continuously monitor, evaluate, and iterate to improve system performance, reliability, and cost efficiency.
• Design and implement scalable, secure, observable, cloud-based solutions.
• Own production systems, including debugging, enhancements, and ongoing optimization.
• Collaborate closely with product and business stakeholders to translate requirements into high-impact solutions.

• 5+ years of software engineering experience (backend or full-stack).
• Proven daily use of AI-native development workflows (e.g., Cursor, Claude Code) for production systems.
• Hands-on experience building production AI agents, including RAG, multi-agent orchestration, tool-calling, structured outputs/validation, memory, and workflow management.
• Experience with agent orchestration and evaluation frameworks (LangChain, LangGraph, LangSmith, Semantic Kernel or equivalent).
• Track record of deploying LLM-powered systems in production.
• Strong backend and modern frontend development skills for complex workflows.
• Experience with cloud services (Azure, AWS, or GCP) and designing scalable architectures.
• Familiarity with vector databases and embedding pipelines.
• Deep understanding of system design, scalability, observability, and security best practices.
• Experience leading small development teams or owning a technical domain.
• Excellent communication, stakeholder management, and problem-solving skills.
• Fluent written and verbal English.
• Experience building AI systems in regulated or compliance-driven environments.
• Background working with internal teams and platforms (e.g., customer service, retention, operations, 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 systems.