AI Engineer

📋 Description

• Design agent loops encompassing planning, memory, retrieval, tool utilization, and self-verification.

• Develop tools such as functions, APIs, database queries, and file interfaces, following MCP-style guidelines.

• Integrate RAG with agents through methods like chunking, embeddings, retrieval, reranking, and grounding.

• Establish guardrails including execution sandboxes, permission settings, rate limits, and policies for handling personally identifiable information (PII).

• Create evaluation metrics for agents focusing on task success, depth of autonomy, and recovery rates.

• Enhance optimization for reliability, determinism when required, and cost efficiency.

⛳️ Requirements

• Experience in production with LangChain, CrewAI, or comparable platforms, particularly in function and tool invocation.

• Proficient in Python engineering, including asynchronous programming patterns and robust error management.

• Hands-on experience with RAG techniques, including vector databases, indexing pipelines, and tuning for retrieval quality.

• Strong systems thinking skills, encompassing concepts such as queues, retries, idempotency, caching, and concurrency control.

• Knowledge of security and safety measures for agents, addressing prompt injection, tool scoping, and the principle of least privilege.

• Nice-to-Haves

• Familiarity with GCP or AWS, Docker or Kubernetes, and messaging buses or streams.

• Understanding of LLM evaluation frameworks and synthetic data generation.

• Experience with graph-based planning, constraint solvers, or program-of-thought methodologies.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Flexible work hours and remote work options.

• Opportunities for professional development and continuous learning.

• Health, dental, and vision insurance plans.

• A vibrant company culture that fosters innovation and collaboration.