AI Native Software Engineer
Listed on 2026-07-21
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Software Development
AI Engineer (Applied/Software)
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. You are an AI Native Engineer with 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 or owning critical technical areas end‑to‑end as a senior IC.
- Partner directly with client stakeholders — acting as both technologist and trusted advisor.
- Define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains.
- Agent Architecture & Engineering Design: 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 that can be iterated on quickly.
- AI Platform Integration: develop and/or extend abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration and multi‑provider enablement.
- Contribute to shared libraries, SDKs, and patterns that can be reused across clients.
- Cloud‑Native Engineering: 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 for your services in production.
- Domain‑Specific Workflows: tailor and deploy agentic applications across verticals (e.g., finance, healthcare, retail), adapting to domain‑specific processes and constraints.
- Client Engagement: participate in and/or lead design workshops, POCs, and code‑with sessions to shape data‑driven agent workflows with stakeholders, fostering trust and adoption.
- Communicate trade‑offs, risks, and recommendations clearly to both technical and non‑technical audiences.
- Measure & Improve: 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.
- Knowledge Sharing: 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 may be required for this role, ranging from 25% to 75% depending on business need and client requirements.
Qualifications- Engineering experience with cloud‑native systems (APIs, microservices, containerization, serverless).
- Minimum 1 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, must have minimum 6 years work experience).
- 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.).
- Git Hub repo with an agent/plugins you have…
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