AI Native Software Engineer

Company Overview

We are a forward-thinking services company at the forefront of AI-native innovation. We partner with enterprise clients to create next-generation, agent-powered workflows engineered to scale in real-world settings. Our engineers embed deeply with customers, moving projects beyond experimentation into operational reality.

Role Summary

As an AI Native Engineer, you will have a strong foundation in building cloud-native solutions and hands‑on experience designing and deploying agentic systems, especially for enterprise environments. You’re a critical thinker who thrives in ambiguity, delivering concrete results by designing, building, and running AI agents that augment workflows and scale across modern infrastructure. You'll shape how enterprises adopt AI-native engineering by leading complex agentic solutions, developing engineering talent, or owning critical technical areas end‑to‑end as a senior IC.

Responsibilities

• Partner directly with client stakeholders as technologist and trusted advisor. Define use cases, prototype, and deploy robust, secure, operational agentic workflows in complex enterprise domains.
• Design and build enterprise‑ready AI agents incorporating retrieval, orchestration, policy‑based routing, tool invocation, evaluation harnesses, and lifecycle observability.
• Implement resilient, testable, and maintainable agentic workflows for rapid iteration.
• Develop or extend abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) for seamless integration and multi‑provider enablement.
• Contribute to shared libraries, SDKs, and patterns reused across clients.
• Leverage containerization (Kubernetes, Docker), microservices, serverless, event‑driven architectures, CI/CD, and observability stacks to deliver scalable AI‑native systems.
• Own deployment, monitoring, and troubleshooting in production.
• Tailor and deploy agentic applications across verticals (finance, healthcare, retail), adapting to domain‑specific processes and constraints.
• Work closely with client SMEs to translate business workflows into agentic solutions.
• Participate in and/or lead design workshops, POCs, and code‑with sessions to shape data‑driven agent workflows; communicate trade‑offs, risks, and recommendations clearly to both technical and non‑technical audiences.
• Define and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness; iterate rapidly based on data, feedback, and changing requirements.
• Craft reusable patterns, documentation, and best practices that influence internal assets and client roadmaps; contribute to internal communities of practice around AI‑native and agentic engineering.

Travel

Travel may be required for this role. The amount of travel will vary from 25% to 75% depending on business need and client requirements.

Qualifications

• Engineering experience with cloud‑native systems (APIs, microservices, containerization, serverless).
• Minimum one year of hands‑on experience designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production or near‑production environments.
• Experience with modern AI platforms — OpenAI, Claude, Vertex AI, or open‑source models — including building or using abstraction layers for multi‑provider pipelines.
• Strong Python, Java or equivalent experience building 12‑factor applications + Infrastructure as Code (Terraform, Helm).
• Experience in client‑facing communication and collaboration, including leading technical discussions, workshops, or delivery sessions under ambiguity.
• Bachelor's degree in Computer Science, Engineering or equivalent, or equivalent (minimum 12 years) work experience. (If Associate’s Degree, minimum 6 years work experience).

Bonus Points

• Relevant AI certifications or agentic tooling experience.
• Experience as an Agentic / AI Engineer in an enterprise environment.
• Built multi‑agent orchestrations using Lang‑graph, Crew AI, Claude SDK, Open AI SDK, etc.
• GitHub repo with an agent/plugins created.
• Additional AI certifications or experience with agentic tooling and frameworks.
• Defined or worked with enterprise‑grade architectures for compound AI systems, orchestration frameworks, or agent registry / stream‑based architectures.
• Understanding of AI‑native paradigm — blending cloud‑native with generative model architectures — optimizing for performance, modularity, and efficiency.
• Delivered solutions across multiple industries (finance, healthcare) tailoring agentic workflows to industry needs.
• Driven execution across multiple workstreams, ensuring quality, delivery, and alignment with client outcomes.