Senior Software Engineer II, Agentic AI Platform

LVT

$185K — $232K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 6+ years in backend/distributed systems at scale with systems and API design experience.
  • Hands-on experience with Kafka or similar event streaming/log-based architecture.
  • Proven track record of service reliability and observability, including SLOs and alerting setups.
  • Ability to select and operate various storage solutions based on access patterns.
  • Proficiency in Go and/or Python for building APIs and backend services.
  • Familiarity with AWS and Kubernetes, emphasizing open, cloud-portable components.
  • Bachelor's or Master's in Computer Science, Engineering, or equivalent experience.

Responsibilities

  • Harden the event pipeline for production reliability with guarantees and schema enforcement.
  • Ensure reliable dispatch paths to agent and CV workflows and expose event projections.
  • Scale materialized stores for efficient access and data consistency.
  • Own observability metrics, dashboards, and support for the pipeline.

Benefits

  • Comprehensive health, dental, and vision coverage.
  • Retirement benefits with a 401k match up to 4%.
  • Flexible PTO to support work-life balance.
Full Job Description
ABOUT THIS ROLE

LVT is building an agentic AI platform that enables autonomous agents that perceive real-world environments, reason over them, and act. Agents operate on an event pipeline that feeds them what's happening across tens of thousands of edge devices and carries their decisions back out to the field. This role builds and hardens the cloud backbone of that platform the event pipeline agents consume from and act through, and the context stores they query.

You'll own the cloud-side reliability, throughput, and scale of the event pipeline, the router/dispatcher that fans events to intelligence services, the projections that make events queryable (including the agent-facing, MCP-exposed context layer), and the observability that keeps it healthy under load.

You will build the platform that lets agents run reliably at fleet scale. You'll partner closely with the edge team that produces events, the data team that owns the lakehouse you feed, infrastructure/operations who run the managed log and broker, and the engineers building the agent and CV workflows that consume your platform.

ROLE RESPONSIBILITIES
  • Harden the event pipeline: Make the cloud pipeline production-grade consumer reliability, delivery and ordering guarantees, replay, idempotency, dead-letter handling, and schema/contract enforcement at the boundary.
  • Serve the agent layer: Make the dispatch path to agent and CV workflows reliable, and expose the event projections via MCP / agent-facing query interfaces that agents read for context, so the agentic platform has a dependable substrate to run on.
  • Scale ingress and projections: Stand up and scale the materialized stores the pipeline serves from (operational hot store, cold capture into the lakehouse), keeping each projection fit to its access pattern and rebuildable from the log.
  • Observability and operability: Own the signals that make the pipeline supportable, own dashboards, alerting, and feature flags.


OUR IDEAL CANDIDATE
  • Backend / Distributed Systems Depth: 6+ years building and operating backend or distributed systems in production at scale, with strong systems and API design experience.
  • Event Streaming / Log-Based Architecture: Hands-on with Kafka or a comparable log/streaming system; topic and partition design, consumer-group semantics, delivery guarantees, replay, and schema-registry integration.
  • Reliability & Observability: A track record of hardening services for production including SLOs, metrics and alerting, dead-letter and failure handling, and the operational maturity to own on-call trade-offs.
  • Storage & Projection Patterns: Comfortable choosing and operating different stores per access pattern (document/relational hot stores; object storage / lakehouse for cold and analytical).
  • Technical Foundation: Strong in Go and/or Python; experience building APIs and large-scale backend services.
  • Cloud-Native: AWS and Kubernetes, with a bias toward open, cloud-portable components.
  • Education: Bachelor's or Master's in Computer Science, Engineering, or a related field, or equivalent practical experience.


PREFERRED QUALIFICATIONS
  • Building agent-facing or MCP data-access layers, governed query interfaces over operational data for autonomous consumers.
  • Integrating agent or CV runtimes onto an event pipeline as pluggable consumers.
  • Stream-processing frameworks (Benthos/Bento, Flink, or similar).
  • Schema and contract tooling (protobuf/Avro, schema registry).
  • Lakehouse producer experience (Iceberg / S3, CDC); MQTT / IoT ingest at scale (EMQX or comparable).


COMPENSATION

The beginning annual salary range for this role is $185,400 - $232,050 USD and is determined by location, job-related experience, and education/training. Your total earning potential is amplified by a bonus structure tied to meeting goals, and you will become an owner from day one through our employee equity program.

BENEFITS

We believe you do your best work when your whole life is supported. We invest in our crew's health, families, and financial futures with a benefits package designed to support you inside and outside the office. Full-time benefits include, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits (401k match up to 4%), and flexible PTO.

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