Forward deployed Engineer- w2

Seeking a hands‑on AI Native Engineer to design, build, and deploy production‑grade AI‑driven systems within enterprise environments. The role focuses on implementing agent‑based workflows, integrating AI platforms, and delivering scalable cloud‑native solutions.

• Design and implement AI agents, including integrating domain knowledge and tools.
• Build evaluation frameworks for accuracy, latency, and reliability.
• Implement observability and monitoring for agent lifecycle.
• Integrate with AI providers such as OpenAI, Anthropic, Google Vertex, and open‑source models.
• Build abstraction layers to support multi‑model and multi‑provider architectures.
• Optimize model usage for performance, cost, and latency.
• Develop cloud‑native services using serverless and event‑driven patterns.
• Implement CI/CD pipelines and infrastructure‑as‑code (e.g., Terraform, Helm).
• Ensure production readiness, logging, monitoring, and fault tolerance.
• Build and deploy AI‑powered applications aligned to business workflows.
• Integrate AI systems into existing enterprise platforms and APIs; develop backend services and APIs supporting agent workflows.
• Define and execute test strategies for AI systems.
• Measure system performance (latency, throughput, accuracy, cost) and debug and optimize production systems.

• Strong experience with cloud‑native systems (APIs, microservices, containers, serverless).
• Experience building and deploying AI/LLM‑based systems in production (agents, RAG, orchestration).
• Proficiency in Python, Java, or similar backend languages.
• Experience with CI/CD, IaC, monitoring and observability tools.
• Hands‑on experience with AI platforms such as OpenAI, Claude, Vertex AI, or similar.

• Experience with agent frameworks (Lang Graph, Auto Gen, CrewAI).
• Experience designing multi‑agent or distributed AI systems.
• Familiarity with enterprise‑scale system integration.
• Experience optimizing AI workloads for cost and performance.

• 100% hands‑on engineering role (no people management).
• Deliver production‑quality code and deployments.
• Work within existing architecture and engineering standards.
• Collaborate with client and internal engineering teams as needed; participate in technical design discussions.