Job Details
Description
Design, build, and deploy production-grade AI-driven systems within complex enterprise environments.
Job Role
We are seeking a hands-on AI Native Software Engineer to design, build, and deploy production grade AI driven systems within complex enterprise environments.
In this role, you will focus on agent-based architectures, AI platform integration, and cloud native development, delivering scalable, reliable solutions that power real business workflows.
This is a 100% hands-on engineering role, ideal for a senior technologist who thrives at the intersection of AI systems, software engineering, and cloud infrastructure.
Key Responsibilities
- Design, implement, and maintain AI agent workflows, including retrieval augmented generation (RAG), orchestration, tool/function invocation, and policy-based routing.
- Build cloud native backend services and APIs to support AI driven applications and enterprise integrations.
- Implement evaluation, monitoring, and observability frameworks to ensure accuracy, latency, reliability, and system health across AI agent lifecycles.
- Optimize AI and system performance across cost, scalability, and latency dimensions in production environments.
Collaboration Tools or Platforms
- Microsoft Office: Excel, Word, Outlook, Teams.
- AI Platforms & Models: OpenAI, Anthropic Claude, Google Vertex AI, and select open source models.
- Agent & Orchestration Frameworks: LangGraph, AutoGen, CrewAI, or similar.
- Cloud & DevOps Tooling: Docker, Kubernetes, Terraform, Helm, CI/CD pipelines.
Qualification Required
Qualifications
- Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- 8-10+ years of professional software engineering experience with ownership of production systems.
- 3+ years of hands-on experience building and deploying AI/LLM based systems in production, including agents, RAG pipelines, and orchestration.
- Strong experience designing and delivering cloud native systems, including APIs, microservices, containers, and serverless or event driven architectures.
- Proficiency in Python, Java, or comparable backend languages.
- Hands-on experience with CI/CD pipelines, infrastructure as code, and monitoring or observability tools.
- Proven ability to deliver production quality code, including testing, debugging, performance tuning, and operational readiness.