Software Engr II

Responsibilities

• Design and develop production-grade Generative AI and Agentic AI applications.
• Build autonomous and semi-autonomous AI agents that can reason, plan, use tools, and collaborate with other agents.
• Develop advanced RAG pipelines leveraging vector databases, embeddings, and enterprise data sources.
• Create multi-step reasoning workflows combining deterministic business logic with LLM-generated reasoning.
• Implement short-term and long-term memory architectures for persistent contextual interactions.
• Design and maintain resilient AI workflows incorporating self-correction, failure recovery, debugging loops, and Human-in-the-Loop (HITL) controls.
• Integrate LLMs, VLMs, enterprise APIs, databases, and external tools into agent ecosystems.
• Deploy and manage AI applications across cloud, hybrid, and on-premises environments.
• Collaborate with product, engineering, and domain experts to translate business requirements into scalable AI solutions.
• Ensure production readiness through monitoring, testing, performance optimization, and governance controls.
• Required Technical Skills & Experience
• Programming & Software Engineering
• Strong proficiency in Python.
• Experience designing and implementing enterprise-grade software solutions.
• Familiarity with software engineering best practices, version control, testing, and CI/CD pipelines.
• Generative AI & Agentic AI
• Hands-on production experience with agent orchestration frameworks such as LangGraph, OpenAI Agents SDK, or equivalent.
• Deep understanding of foundational agentic design patterns, including: Reflection Tool Use Planning Multi-Agent Collaboration
• Reflection
• Tool Use
• Planning
• Multi-Agent Collaboration
• Practical experience with: Function calling Structured outputs Prompt engineering Context window management
• Function calling