Maintain and improve the internal flows, services, and modules that enable the AI agent to operate stably and efficiently.
Implement technical optimizations aimed at improving performance, resource usage, and response times.
Diagnose, resolve, and prevent agent-related incidents, including root cause analysis and hardening actions.
Develop test agents, experimentation environments, and A/B variants that enable continuous technical iteration.
Perform technical prompt engineering adjustments (context, parameters, configurations) necessary for the agent's operation.

5+ years of professional experience developing and maintaining backend systems in production.
Mastery of Python as the primary language for service development.
Experience with distributed systems, concurrency control, message queues, and event-driven architectures (SQS, Redis streams/queues, background workers).
Experience building and integrating backend services that expose structured tools to LLMs (e.g., MCP servers or similar tools) and with systems that integrate LLM-based agents.
Previous experience working with LLM-based systems or agents, adjusting the technical configurations necessary for their operation.
Solid knowledge of SQL and relational databases.
Experience working with AWS (Bedrock, ECS, Lambda, RDS, S3, IAM).
Experience using Datadog for logs, metrics, and traces in backend systems, or similar observability tools.

Senior Software Engineer

Key skills