AI Engineer, Agent Analytics & Optimization (DPI)

Conviva•Foster City, CA

6d•$180,000 - $250,000•Hybrid

About The Position

Conviva is a leader in understanding and optimizing digital customer experiences through its Operational Data Platform. This platform captures comprehensive client-side telemetry to provide AI-powered insights into user experience and engagement across all devices. The role of AI Engineer, Agent Analytics & Optimization focuses on building the systems that enable AI agents to interact with Conviva's behavioral data. This involves designing, developing, and deploying production-grade systems, including MCP servers, agentic workflows, and AI connectors. The engineer will be responsible for the full lifecycle of these systems, from API design to deployment, monitoring, and iteration, working closely with product teams and customers. This is a hands-on engineering role focused on building reliable, scalable systems rather than research or prompt engineering.

Requirements

3–7+ years of software engineering experience, with production systems shipped end-to-end.
Strong Python backend fundamentals; comfortable owning services from design through deployment (fullstack a plus).
Hands-on experience building and operating LLM-powered agents in production.
Practical familiarity with agentic patterns: tool use, structured outputs, prompt chaining, multi-agent coordination, and knowing when a deterministic workflow is the right call.
Experience designing/building MCP servers or equivalent tool-use / AI connector integrations.
Have used evals to validate and debug agent behavior.
Comfortable with cloud deployment (GCP/AWS), containerized services, and async Python.
Strong product instinct — thinks about what users actually need and pushes back when a spec doesn't add up.

Nice To Haves

Experience with agentic frameworks (LangGraph, Anthropic SDK, Pydantic-AI, CrewAI, or similar).
Agent observability/tracing (Langfuse, LangSmith, OpenTelemetry, or homegrown).
Background in digital experience analytics, observability, or APM.
Familiarity with agent evaluation or LLM-ops tooling.
Published writing, talks, or open-source work at the intersection of engineering and AI.

Responsibilities

Design and build MCP servers that expose Conviva's data and analytics as discoverable, reliable tools for AI agents, with proper authentication, scoping, and access controls.
Architect and ship agentic workflows, including multi-step reasoning, tool use, orchestration patterns, and human-in-the-loop processes.
Develop AI connectors to integrate Conviva's intelligence with external agents, clients, and downstream systems.
Own the full lifecycle of agentic systems, including API/tool design, deployment, monitoring, and production hardening.
Use evals to validate agent behavior before shipping, catch regressions, and debug production divergence.
Build observability and tracing to make agent behavior inspectable and auditable.
Tune systems for latency, cost, and reliability as models and data drift.
Partner with Product Builders, design, and customers to ship working software.
Build internal SDKs, reusable patterns, and shared context to improve team efficiency.
Stay informed about the fast-moving MCP/agent ecosystem and apply relevant advancements.