Principal / Staff AI Engineer

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

About the Product:
We are building and scaling a mature, data-intensive B2B SaaS platform used by enterprise customers across multiple markets. The platform supports a diverse range of enterprise use cases across operational planning, information analysis, case management, and cross-team collaboration.
The product brings together large volumes of structured and unstructured data, domain-specific analytics, and configurable workflows to help users investigate complex cases, collaborate effectively, and make timely operational decisions.

About the Role:
We are looking for a Principal / Staff AI Engineer to design, build, and deliver reliable AI-powered capabilities as part of an established production platform.
You will work at the intersection of backend engineering, generative AI, and product development. Your responsibilities will cover the full delivery cycle – from exploring ideas and validating technical approaches to building production services, evaluating output quality, and improving solutions based on real-world usage.
This is a hands-on engineering role with significant ownership. You will have the opportunity to influence architectural decisions, engineering practices, and the broader adoption of AI across the product while working closely with engineering, product, and other cross-functional teams.

Key Responsibilities:
Design, build, and deploy production-grade autonomous agent systems that solve open-ended, complex, and multi-step tasks for real users.
Build the core agent platform and harness, including planning, tool use, agent orchestration, context management, memory, and reusable agent skills.
Develop agents that can independently determine their next steps, adapt based on intermediate results, and maintain direction during long-running tasks.
Design human-in-the-loop mechanisms that define when agents can act independently and when human guidance, review, or approval is required.
Develop methods and tooling to validate AI-generated results, evaluate agent behavior, diagnose failures, monitor production performance, and improve reliability over time.
Build scalable Python backend services and integrate agent capabilities with distributed production systems, taking new functionality from experimentation to reliable real-world use.
Own key architectural and technical decisions, establish AI engineering standards, and introduce new approaches that advance the team’s agent platform and engineering expertise.
Required Competence and Skills:
7+ years of software engineering experience, including at least 1.5 years of hands-on experience building and shipping LLM-based products to production.
Proven experience building autonomous AI agent systems used by real users at meaningful scale and capable of handling complex, open-ended, multi-step tasks.
Hands-on experience with AI agent frameworks such as LangChain, LangGraph, Deep Agents, or similar. Experience selecting frameworks, identifying their limitations, and building custom components where needed.
Strong backend engineering skills in Python or another language such as Golang, Java, or Rust, with the willingness to work primarily with Python.
Experience with context and memory management, agent orchestration, and human-in-the-loop systems.
Experience taking AI products from experimentation to reliable production use, including cloud deployment, system integration, AI quality validation, monitoring, and agent failure analysis.
Strong end-to-end ownership, communication, and ability to make technical decisions, work independently, and adapt quickly in a high-velocity environment.
Advanced English skills.
Nice to Have:
Experience with React.js and full-stack development, with the ability to contribute to frontend development when needed.
Experience with vector databases and similarity search in production AI applications.