Senior Engineer, AI/ML

About this role

We operate a multi-tenant automotive SaaS platform serving thousands of dealer groups across the United States, running on a native AWS (NAWS) backend: Lambda, EventBridge, DynamoDB, S3, Step Functions. That platform works. Now we are making it think: production agentic AI systems built code-first and deployed on AWS Bedrock AgentCore, connected to real systems, making decisions and executing workflows against real dealer data and real money. This is a hands-on builder role. Expect the large majority of your time in code. But we are not hiring a pair of hands. Every agent you ship makes decisions that touch dealer revenue, so we need an engineer who understands the business problem before writing the technical solution: someone who asks what a workflow is worth, weighs build cost against dealer impact, and knows when the right answer is a simpler tool, or no agent at all. What you will own: Building production agents in Strands/LangGraph on AgentCore: agent logic, tool orchestration, and multi-agent workflows deployed on AgentCore Runtime with Memory, Identity, and Gateway. Tool interfaces: framework-agnostic Python tools, MCP servers, and AgentCore Gateway targets that let agents safely call production APIs. Evaluation harnesses: offline/online eval pipelines and LLM-as-judge CI/CD gates that catch regressions before dealers do. Guardrails and safe failure: approval gates and rollback paths that determine whether an agent fails safe or fails loud. Cost and latency management: per-agent cost tracking and multi-model routing so each workflow earns more than it costs. Production observability: AgentCore session tracing, OpenTelemetry, and CloudWatch dashboards for every agent you ship. Tech environment: Strands Agents SDK on AWS Bedrock AgentCore (Runtime, Gateway, Memory, Identity, Observability); MCP servers; Bedrock Guardrails; Anthropic models (Haiku, Sonnet, Opus); NAWS stack (Lambda, EventBridge, DynamoDB, S3, Step Functions, ECS Fargate, Aurora, API Gateway, CDK); Python primary, Java (Spring Boot) secondary. You work within the platform's established architectural patterns, and produce deliverables using agentic frameworks, AWS serverless core, MCP/tool design, and observability without someone looking over your shoulder. Prompt engineering and tool-use design are core engineering disciplines here, not an afterthought. Scope and scale: 5,000+ destination dealer tenants, each with isolated databases and per-tenant configuration. Agent workflows that touch production transaction data: real dealer money, not a sandbox. Tens of thousands of API requests across REST, SOAP, and event-driven integration surfaces that your agents' tools will call into. A growing portfolio of production agents, each with its own cost, latency, and evaluation budget. Your first 6 months: Month 1: Ramp on the platform architecture, existing agents, and integration surfaces, and on the dealer workflows behind them, so you know what the agents are for, not just how they run. Ship your first tool integration (MCP server or Gateway target) to production. Months 2-3: Own end-to-end agent workflows, from design through production on AgentCore: Strands agent logic, tool interfaces, evaluation harness with CI gates, and guardrails. Months 4+: Running autonomously: shipping new agents and tools with minimal oversight, with observability and cost tracking in place for everything you own. Requirements Must have: 5+ years of software engineering experience, including hands-on production experience building LLM agents in a code-first framework. Strands Agents and LangGraph are equally acceptable, as are Google ADK, OpenAI Agents SDK, and comparable frameworks. If you have built and operated real agents in any of them, you will pick up Strands quickly. Business-conscious judgment: you start from the problem and its value, not the technology, and you have walked away from a clever solution because a simpler one served the customer better. Strong Python; ability to read and contribute to Java (Spring Boot) services. Hands-on experience with AWS serverless (Lambda, EventBridge, DynamoDB, Step Functions). Experience with prompt engineering, tool/function-calling design, and evaluating LLM output quality in production. An appetite for a heads-down building role: you measure your week in shipped code. Strongly preferred: Direct experience with Strands Agents and/or AgentCore Runtime (or migrating agent workloads from Lambda/Fargate to a managed agent runtime); LLM-as-judge, agent-to-agent orchestration, and agent governance. Direct production experience with MCP (Model Context Protocol) servers. Comfort owning production observability (OpenTelemetry, CloudWatch) for the systems you build. Nice to have: Automotive, fintech, or multi-tenant marketplace platform experience. Familiarity with Bedrock Guardrails, LLM-as-judge evaluation, model cost/latency optimization, and multi-agent orchestration patterns. Experience with data pipelines (Glue/Athena) or ETL/data lake tooling. Benefits About A2Z Sync A2Z Sync is a fast-paced and innovative automotive SaaS company seeking to make life better for our customers. We offer you a fun, casual, and collaborative culture, while fostering an environment where you work hard, see your results, and feel your impact. We are committed to our employees, and this starts with providing benefits that allow you to care for you and your family. Mission At A2Z Sync, we replace the friction of disconnected systems with the velocity of a single platform. We integrate digital insights with in-store operations to deliver transparent transactions that bring clarity to the car buyer and increased profitability to the dealer. Our Values: We Are DRIVEN Dealership Obsessed: We measure our success by the dealer's wins and the trust of their buyers, not just our own code. Relentless Ownership: No lone wolves, but no pass-backs either. We don't say "that's not my job." Invent with Purpose: We don't chase "shiny" tec