AI Engineer, Agent Analytics & Optimization (DPI)
About The Position
Conviva is seeking an AI Engineer to build the systems that enable AI agents to understand, query, and act on Conviva's behavioral data. This role involves designing and shipping agentic systems from tool interface through deployment, observability, and iteration, working closely with product and customers. The focus is on building production systems that use AI to solve real problems at scale, rather than research or prompt engineering. This is an engineering role distinct from Product Builder roles, focusing on turning product direction into production-grade, reliable systems. Success in this role will involve designing and building MCP servers to expose Conviva's data as reliable tools for AI agents, architecting and shipping agentic workflows (multi-step reasoning, tool use, orchestration), and developing AI connectors for integrating Conviva's intelligence with external systems. The engineer will own the full lifecycle, including API/tool design, deployment, monitoring, and production hardening. Reliability and iteration are key, utilizing evals for validation, building observability and tracing, and tuning for performance as models and data evolve. Execution and collaboration with Product Builders, design, and customers are essential, as is building internal SDKs and staying current with the MCP/agent ecosystem.
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 — with concrete stories of what broke, how you fixed it, and what you'd do differently
- 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 auth, scoping, and access controls
- Architect and ship agentic workflows: multi-step reasoning, tool use, orchestration patterns, and human-in-the-loop where needed
- Develop AI connectors integrating Conviva's intelligence with external agents, clients, and downstream systems
- Own the full lifecycle — API/tool design, deployment, monitoring, 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 for latency, cost, and reliability as models and data drift
- Partner with Product Builders, design, and customers to ship working software (not prototypes)
- Build internal SDKs, reusable patterns, and shared context that raise the floor for the whole team
- Stay close to the fast-moving MCP/agent ecosystem and bring back what's relevant
Benefits
- Competitive compensation, equity, and benefits
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
