AI Native Software Engineer

Position 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. 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. Depending on level, you may lead the design and delivery of complex agentic solutions and mentor/coach other engineers, or serve as an individual contributor owning key technical areas end to end. In all cases, you’ll help shape the playbook for how enterprises adopt and scale AI-native engineering.

Key Responsibilities

• 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 that can be iterated on quickly.
• 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.
• 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.
• Tailor and deploy agentic applications across verticals (e.g., 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, proofs of concept, and code-with sessions to shape data-driven agent workflows with stakeholders.
• 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.

Required Qualifications

• Minimum of 3 years of engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
• Minimum of 1 year of hands-on experience designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production or near-production environments.
• Minimum of 1 year of experience with modern AI platforms — OpenAI, Claude, Vertex AI, or open-source models — including building or using abstraction layers for multi-provider pipelines.
• Minimum of 3 years programming experience in Python, Java, or equivalent, with familiarity in evaluation tooling, logging, monitoring, and agent observability.
• Minimum of 3 years of experience deploying to production using CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging.
• Minimum of 3 years of experience in client-facing communication and collaboration, including leading technical discussions, workshops, or delivery sessions under ambiguity.
• Education: 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)

Preferred Qualifications

• Relevant AI certifications or agentic tooling experience are a plus.
• Experience serving as an Agentic / AI Engineer in an enterprise environment.
• Additional AI certifications or experience with agentic tooling and frameworks.
• Experience with enterprise-grade architectures for compound AI systems, orchestration frameworks, or agent registry/stream-based architectures.
• Understanding of the AI-native paradigm — blending cloud-native with generative model architectures — optimizing for performance, modularity, and efficiency.
• Experience delivering solutions across multiple industries (e.g., finance, healthcare) by tailoring agentic workflows to industry needs.
• Experience leading a small team of engineers, providing coaching, feedback, and career development.
• Proven track record in driving execution across multiple workstreams, ensuring quality, delivery, and alignment with client outcomes.

Benefits & Perks

• Medical, dental, vision, life, and long-term disability coverage
• 401(k) plan
• Bonus opportunities
• Paid holidays and paid time off
• Compensation: Varies depending on office location, role, skill set, and experience