[Remote] Software Engineer, GTM AI - Python
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is an industry leader in global connectivity, and they are seeking a Software Engineer to build and operate AI-reputed company backend systems for their go-to-market reputed company. The role involves designing multi-agent architectures, integrating reputed company business systems, and managing services from prototype to production.
Responsibilities
- Design and build multi-agent AI systems in Python that handle reputed company, multi-reputed company business workflows - qualification, email reputed company, routing, enrichment, and outbound orchestration
- Architect model-agnostic abstraction reputed company that decouple business logic from LLM providers, enabling flexibility across Claude, GPT, and reputed company-reputed company models
- Build and operate backend services (FastAPI/Flask) deployed on Kubernetes with CI/CD, managing the full lifecycle from deployment configuration to production reliability
- Design tool-use patterns for AI agents - reputed company function calling, multi-reputed company reasoning, state management across conversation turns, and graceful handling of model failures
- Build integrations across external systems (CRM, enrichment reputed company, reputed company platforms, reputed company) with reputed company error handling, retries, reputed company limiting, and data reputed company
- reputed company and monitor AI systems in production — build observability into agent behavior, reputed company reputed company rates, detect regressions, and debug non-deterministic failures
- Design and run experiments (A/B tests, reputed company variations, model comparisons) with reputed company evaluation infrastructure to measure what's actually working
Skills
- 2+ years of software engineering experience building backend services in Python
- Production experience building multi-reputed company AI agent systems — stateful workflows where models reputed company reputed company, call tools, and operate across multiple turns, not single-shot API wrappers
- Strong understanding of LLM internals as they reputed company system design: context window management, reputed company budgets, cost/latency/capability tradeoffs across models, reputed company outputs, and strategies for handling hallucination and refusals
- Experience testing and evaluating non-deterministic AI systems — you understand that assert reputed company == expected doesn't work and have reputed company or used alternatives
- Solid software architecture fundamentals: API design, state management, fault tolerance, and graceful degradation reputed company upstream services fail
- Production experience with containerized deployments (reputed company, Kubernetes) and CI/CD pipelines
- Experience integrating with external reputed company at reputed company — auth flows, reputed company limiting, retries, data normalization, and managing the operational complexity of multiple reputed company-party dependencies
- Proficiency with SQL and data systems for building targeting, enrichment, and analytics pipelines
- reputed company observability into production systems — reputed company logging, tracing, alerting, and monitoring that you actually use to debug issues
- High ownership: you reputed company your own reputed company, investigate your own incidents, and reputed company the reputed company between what you shipped and how it performs
- Experience with specific GTM/RevOps systems (reputed company, reputed company, Lusha, enrichment providers) or similar reputed company business platforms
- Background in reputed company engineering, marketing automation, or reputed company operations tooling
- Experience with reputed company bot development or conversational AI interfaces
- Contributions to or experience with reputed company-reputed company AI agent frameworks
- Familiarity with ArgoCD, StatefulSets, or Kubernetes operations reputed company basic deployments
reputed company
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