AI Native Product Engineer & Orchestrator (all gender)

• Product Orchestration: Partner with business and technical stakeholders to frame problems, align priorities, and translate needs into orchestrated AI workflows.
• Agent Architecture & Engineering: Design and engineer enterprise-ready AI agents - including retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
• Creative Problem Solving: Prototype novel solutions that blend technical rigor with human-centered product thinking.
• AI Platform Integration: Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration and enablement.
• Cloud-Native Product & Software Engineering: Apply containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability to create and integrate scalable AI-native systems.
• Domain-Specific Workflows: Tailor and deploy agentic applications across industry verticals (e.g. finance, healthcare, retail) - addressing domain-specific processes via intelligent automation.
• Storytelling & Communication: Lead design workshops, POCs, and code-with sessions; communicate technical tradeoffs and solution impact clearly to both executives and engineers.
• Measure & Improve: Define and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness.
• Knowledge Sharing: Craft reusable patterns, documentation, and best practices to influence internal assets and client roadmaps.

Do you have experience in Terraform?, Do you have a Bachelor's degree?, An AI Native Product Engineer with 3-5 years of experience building cloud-native solutions and orchestrating cross-functional efforts. You combine hands-on engineering depth with the creativity and product intuition to shape solutions that make sense for real users and enterprises. You're as comfortable writing production code as you are whiteboarding system designs, facilitating a client workshop, or mapping a product roadmap. You thrive in ambiguity and act as a bridge between vision and execution., * 3-5 years engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).

• Deep expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.
• Strong experience with AI platforms - OpenAI, Claude, Vertex AI, plus open-source models - including building abstraction layers to manage multi-provider pipelines.
• Strong programming experience in Python, Java, C# or equivalent; familiarity with evaluation tooling, logging, monitoring, and agent observability.
• Experience deploying to production - CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging.
• Excellent client communication and collaboration skills - able to orchestrate across stakeholders, run design workshops, and deliver under ambiguity.
• A creative, product-oriented mindset - you don't just code solutions, you design experiences that stick.
• Bachelor's degree in Computer Science, Engineering, or equivalent; additional AI certifications or agentic tool experience is a plus., * You've served as a Product Engineer, Solutions Architect, or Agentic AI Engineer in an enterprise environment.
• You've defined or worked with enterprise-grade architectures for compound AI systems, orchestration frameworks, or agent registry/stream-based architectures.
• You master the AI-native paradigm - blending cloud-native with generative model architectures - optimizing for performance, modularity, and efficiency.
• You've delivered solutions across multiple industries (e.g., finance, healthcare) by tailoring agentic workflows to industry needs.
• You've demonstrated creative solutioning (e.g., hackathons, product incubation, startup experience).

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 teams embed deeply with customers, orchestrating people, tools, and processes to move projects beyond experimentation into operational reality.