TELECOMMUTE Senior AI/MLEngineer

InfoVision, Inc.
United States
27 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Extract Transform Load (ETL) Amazon DynamoDB Python (Programming Language) Software Engineering Large Language Models Multi-Agent Systems Prompt Engineering Spring-boot Data Lakes AWS Fargate Cloudwatch
+2 more
Data Pipelines Serverless Computing

Requirements

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.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

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