Applied AI Engineer - Agentic Systems

About DeepLight AI

The opportunity

Responsibilities

• Design agent loops, state machines, and tool-calling mechanisms for complex enterprise tasks.
• Build context-management pipelines and RAG modules grounded in dynamic enterprise knowledge sources.
• Integrate LLMs and agents with enterprise databases, legacy applications, APIs, and modern protocols such as MCP.
• Write production-ready Python with automated tests, structured-output validation, fallback logic, and human-in-the-loop controls.
• Instrument end-to-end tracing and evaluation to benchmark quality, diagnose hallucination loops and latency, and optimize token costs.
• Collaborate with client teams and business sponsors on technical designs, acceptance criteria, and system architectures.
• Present and explain technical decisions and advocate for solutions to stakeholders.

What the employer is looking for

• Demonstrable experience implementing AI agents, multi-agent frameworks, tool calling, and state management.
• Advanced Python proficiency, including maintainability, pytest, code reviews, and Git.
• Practical LLM API integration, prompt design, structured-output validation, and model/tool failure handling experience.
• Experience with LLM evaluation, representative task sets, failure analysis, regression testing, and tracing tools.
• Ability to balance reasoning quality, reliability, latency, and operational cost.
• Candidates should be prepared to discuss a system they personally built, its trade-offs and evaluation, limitations, and path from prototype to production.

Advantageous experience

• Deploying and supporting LLM agents used by business teams or external customers is advantageous.
• Familiarity with LangGraph, AutoGen, CrewAI, LlamaIndex Workflows, or custom state machines is advantageous.
• Hands-on MCP, Docker, and AWS or Azure deployment experience is advantageous.
• Regulated enterprise delivery experience, such as banking, financial services, or insurance, is advantageous.

Benefits

• Competitive salary, health insurance, visa sponsorship, professional development and certification support, and role-related subscription reimbursement.
• Monthly employee incentive program, career advancement opportunities, and work on AI projects.

Interview process

• The employer aims to make the application and interview process accessible and fair; candidates may request reasonable adjustments.