We are seeking a talented Senior Python Engineer to join our dynamic team.
What is this project about? An AI-powered analytics platform built for the defense domain. It ingests and analyzes data from multiple sources, automatically surfacing key findings and generating actionable insights and recommendations. By automating heavy manual analysis, the platform helps organizations make faster, better-informed decisions, reduce manual effort, and improve overall operational performance.
What is the team size and structure? Architect, Project Manager, ML Engineers, UI/UX Designer, DevOps, Business Analyst.
What is the interview process like? Recruiter interview — up to 30 minutes; Technical interview — up to 1.5 hours; Polygraph screening.
Requirements:
● 5+ years of experience in backend development; ● Solid experience with Python and modern backend frameworks; ● Strong understanding of distributed architecture; ● Experience building APIs, integrations, background workers, and data processing services; ● Experience with async processing, queues, scheduled jobs, and long-running workflows; ● Understanding of agent-based systems, workflow orchestration, and task execution pipelines; ● Good understanding of LLM-based systems and the separation between LLM logic and deterministic backend logic; ● Experience working with structured and unstructured data; ● Understanding of databases, object storage, vector databases, and data pipelines; ● Experience with performance optimization, scalability, and fault-tolerant backend design; ● Understanding of security basics: authentication, authorization, RBAC, audit logging, and secure data handling; ● Ability to write clean, maintainable, testable, and well-structured code; ● High level of ownership, proactivity, and engineering discipline; ● Intermediate level of English.
Nice to have: ● Experience in AI, data-heavy platforms, or Defense/MilTech domains.
Responsibilities: ● Implement backend services, APIs, integrations, and data processing components; ● Develop core business logic and deterministic processing outside the LLM layer; ● Implement agent runtime components and support agent workflow execution; ● Build and maintain services for data ingestion, transformation, validation, and enrichment; ● Integrate backend services with the inference layer, orchestration layer, data layer, and external systems; ● Implement task execution logic, background jobs, queues, and long-running workflows; ● Work with structured outputs from LLMs and validate them before further processing; ● Implement APIs for frontend, internal services, data access, and automation components; ● Optimize backend services for latency, throughput, reliability, and scalability; ● Ensure proper error handling, retries, logging, monitoring, and auditability; ● Participate in technical design, estimation, refinement, and code reviews; ● Write unit, integration, and API tests; ● Support debugging, performance analysis, and production issue investigation; ● Collaborate with the Architect, ML/AI engineers, DevOps, QA, BA, and Product Owner; ● Maintain backend documentation, API contracts, and implementation notes.
