Senior Agent Engineer Job Summary :
- We are seeking a Senior AI Agent Engineer who is, first and foremost, a strong software engineer with applied Machine Learning expertise.
- Unlike a pure Data Science role, this position requires deep production engineering skills to build, scale, and evaluate robust AI agentic workflows integrated directly into our core backend.
- You will leverage LLMs and software best practices to create autonomous systems that are reliable, observable, and production-ready.
Key Responsibilities :
Agent Architecture & Orchestration : Architect end-to-end AI agent systems capable of multi-step reasoning, planning, and self-correction.Design complex control flows (loops, conditionals, DAGs) rather than simple linear chains.Production Engineering & Integration :
Integrate agents seamlessly into production backends.Build robust integrations enabling agents to use APIs, databases, and vector stores with strict data validation.State & Memory Management :
Design systems to manage agent context windows, conversation history, and long-term memory (Vector DBs) efficiently to balance performance and cost.Reliability & Evaluation (Core Focus) :
Apply engineering rigor to agent reliability.Design evaluation pipelines (e.g., LLM-as-a-judge, functional unit tests) to quantify performance and handle the non-deterministic nature of LLMs.System Scalability & Economics :
Optimize agent workflows for latency and token usage costs.Implement caching, retries, and async processing to ensure high throughput.Observability & Monitoring :
Instrument code to provide deep visibility into agent reasoning steps (tracing), ensuring failures can be debugged in production environments.Data Analysis and Reporting :
Extract data using SQL and Python and conduct comprehensive data analysis to identify trends, anomalies, and patterns.Required Skills and Qualifications :
Education : Bachelor's or Master's in CS, AI, or equivalent practical experience.Software Engineering Mastery :
Deep expertise in Python, system design, testing, Git, and deploying production-grade services.This is an engineering-heavy role.Backend Infrastructure :
Proven experience developing and maintaining backend infrastructure (AWS / Azure / GCP) and containerization (Docker / Kubernetes).Agentic Frameworks :
Hands-on experience with frameworks such as LangChain, LlamaIndex, LangGraph, CrewAI, or AutoGen.Applied ML & RAG :
Experience with grounding techniques (RAG, vector search), prompt engineering, and utilizing Embeddings APIs.Evaluation Rigor :
Experience building automated evaluation harnesses to test agent logic against "Golden Datasets." Problem-Solving : Excellent analytical skills to debug complex, non-deterministic system failures.Team Mentorship :
Ability to inspire, motivate, and mentor fellow team members through activities such as code reviews and technical meetings.Nice-to-Have :
Familiarity with neural network fundamentals (e.g., Transformers).Experience with LLM Observability tools (e.g., LangSmith, Arize Phoenix).Understanding of LLM security (e.g., prompt injection defense).Powered by JazzHR