AI Native Software Engineer Senior Analyst

Role Overview

Agent Architecture and Engineering

• Design and build enterprise-ready AI agents using retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
• Implement resilient, testable, and maintainable agentic workflows that can be rapidly iterated.

AI Platform and Cloud Engineering

• Develop or extend abstraction layers across AI providers, including Anthropic, Google, and OpenAI, for multi-provider enablement.
• Contribute reusable shared libraries, SDKs, and engineering patterns across clients.
• Use Kubernetes, Docker, microservices, serverless, event-driven architectures, CI/CD, and observability stacks to deliver scalable systems.
• Own production deployment, monitoring, and troubleshooting for services.

Client and Domain Delivery

• Tailor and deploy agentic applications across sectors such as finance, healthcare, and retail.
• Work with client subject-matter experts to translate business workflows into agentic solutions.
• Lead or participate in design workshops, POCs, and code-with sessions with stakeholders.
• Communicate technical trade-offs, risks, and recommendations to technical and non-technical audiences.

Measurement and Knowledge Sharing

• Define metrics, test harnesses, and evaluation plans for agent accuracy, latency, safety, and cost effectiveness.
• Iterate based on data, feedback, and changing requirements.
• Create reusable patterns, documentation, and best practices for internal assets and client roadmaps.
• Contribute to communities of practice around AI-native and agentic engineering.

Required Qualifications

• Experience with cloud-native systems, including APIs, microservices, containerization, and serverless architectures.
• Hands-on experience designing and deploying agentic solutions with agents, orchestration, context engineering, RAG, and workflow automation.
• Experience with modern AI platforms such as OpenAI, Claude, Vertex AI, or open-source models and multi-provider AI pipeline abstractions.
• Strong Python, Java, or equivalent programming expertise.
• Experience building 12-factor applications and Infrastructure as Code with tools such as Terraform and Helm.
• Proven client-facing communication, collaboration, technical discussion, workshop, and delivery skills.
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Preferred Qualifications

• Relevant AI certifications or agentic tooling experience.
• Enterprise experience as an Agentic or AI Engineer.
• Experience building multi-agent orchestrations with LangGraph, CrewAI, Claude SDK, or OpenAI SDK.
• A GitHub repository containing created agents or plugins.
• Experience with enterprise-grade compound AI architectures, orchestration frameworks, agent registries, or stream-based architectures.
• Understanding of AI-native engineering combining cloud-native and generative model architectures.
• Experience delivering industry-tailored agentic workflows across multiple sectors.
• Experience driving execution across multiple workstreams while maintaining quality and alignment with client outcomes.

Travel

• Travel may be required and may range from 25% to 75% based on business needs and client requirements.