Senior AI Engineer
Build and deploy production-grade agentic AI systems and automation workflows that drive efficiency across sales, marketing, finance, and other business functions. Partner with stakeholders to identify high-impact use cases and deliver reliable, observable LLM-powered solutions.
About the job
What You'll Do
Prioritization of High-Impact Automation
- Partner with business teams (e.g., Revenue Ops, Marketing, Finance Ops, Talent Acquisition) to catalog manual, high-frequency workflows and rank them by impact, feasibility, and urgency.
Production Agent Design & Development
- Build multi-step, tool-augmented agent workflows that can plan, execute, observe outcomes, and iteratively improve.
- Design and implement planner–executor and reflection-based architectures to enhance reasoning quality and task reliability.
- Develop stateful agent systems and incorporate human-in-the-loop controls, including approval gates, fallback paths, and escalation mechanisms.
Platform Integration
- Leverage the Agentic AI Foundations team's platform covering agent runtime, orchestration, memory, tool registry, guardrails, and observability.
- Provide feedback that shapes platform priorities.
Innovation & Standards
- Leverage LLMs, multi-agent frameworks, and orchestration platforms to create differentiated internal solutions.
- Stay ahead of emerging AI technologies and regulatory frameworks.
Technical Patterns
- Discover reusable agent design patterns while building real workflows and contribute them back to the Agentic AI Foundations paved paths.
Operational Excellence
- Leverage the evaluation harness and tracing substrate for continuous performance assessment, failure-mode analysis, and optimization of speed and accuracy.
What We're Looking For
Required
- 8+ years of software engineering experience, with at least 2 years focused on AI/ML systems or LLM-powered applications in production.
- Deep hands-on experience with LLM APIs and at least one agentic framework (e.g. LangGraph, CrewAI or AutoGen).
- Strong Python skills and experience building production-grade backend services, APIs, and data pipelines.
- Proven ability to operate in ambiguity: walked into an undefined problem space, figured out what to build, built it, and measured the results.
- Experience shipping AI/automation solutions that directly impacted business operations.
- Strong systems thinking: design for reliability, observability, and maintainability from day one.
- Ability to collaborate directly with non-technical business stakeholders to understand their workflows and translate those into technical solutions.
Preferred
- Experience with multi-agent systems, workflow orchestration, or complex tool-use patterns in production.
- Familiarity with evaluation frameworks (e.g., LangSmith, Weights & Biases, Arize, or custom eval pipelines).
- Experience with RAG pipelines, vector databases, knowledge graphs, or memory/grounding systems.
- Experience with real-time or streaming AI systems.
- Familiarity with AI safety and security practices, including prompt injection prevention, hallucinations mitigation and data protection/privacy.
- Background in a regulated industry (fintech, healthcare, government).
- Experience with agent skill abstraction and structured tool integration via MCP (Model Context Protocol), function calling or similar protocols.
- Experience with AWS-hosted LLM infrastructure (Bedrock, AgentCore/Strands, Lambda, SageMaker).
Skills
Python, LangGraph, Crewai, Autogen, LLM APIs, RAG, Vector Databases, Langsmith, Aws Bedrock, SageMaker, Multi-Agent Systems, Workflow Orchestration
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