(USA) Principal, Software Engineer

Position Summary...

What you'll do...

About the Role:

We are looking for a Principal Software Engineer who is an architect-level expert in Python, with a deep mastery of LLM-driven systems, agentic architectures, and scalable intelligent automation. This is a pivotal role where you'll define the technical strategy, influence architecture across domains, and lead the creation of next-gen AI-driven platforms that move beyond prompt engineering into modular reasoning systems.

This role isn’t about building one-off workflows—it’s about inventing and hardening intelligent systems that can reason, act, and adapt. You will shape the core architecture of multi-agent platforms, ensure LLM integrations are secure, efficient, and observable, and build frameworks that others can extend across use cases and orgs.

As a Principal Engineer, you set the vision, write the critical path code, guide Staff and Senior engineers, and are the final word on whether a design is ready for scale.

Key Responsibilities:

• Define and own the agentic architecture strategy across teams, including MasterAgent design, tool orchestration, memory layers, and dynamic router agents.

• Architect modular, testable, and composable Python systems that support multi-agent workflows, tool-chaining, RAG, memory management, and fallback strategies.

• Design LLM-powered execution engines that support both high throughput and adaptive reasoning (via LangChain, AutoGen, or custom frameworks).

• Lead implementation of retrieval-augmented generation (RAG) pipelines, semantic search, and structured knowledge memory systems.

• Build and scale integrations with internal LLMs, including handling signature-based auth, function calling, and context management at scale.

• Drive end-to-end lifecycle: from configuration schema (YAML) to execution trace logging, observability, and self-healing recovery patterns.

• Lead cross-org architecture reviews, influence roadmap prioritization, and set coding and design standards for all agentic platform work.

• Act as a multiplier by mentoring Staff/Senior engineers, building reusable libraries, and leading technical guilds around AI agent infrastructure.

Must-Have Qualifications:

• 10+ years of professional software engineering experience, with 7+ years in Python, building distributed systems at scale.

• Deep knowledge of agentic design patterns, including:

• ReAct, Plan-and-Execute, AutoGen-style coordination

• Tool calling, dynamic agent routing, and recursive agent planning

• Semantic memory, embedding-based context lookup, summarization windows

• Expertise in building LLM-based systems with LangChain, OpenAI, Anthropic, or custom orchestrators.

Hands-on experience with:

• RAG pipelines using vector stores (FAISS, Pinecone, Weaviate, Qdrant, Azure Cognitive Search)

• LLM evaluation and observability (tracing, token usage, agent state tracking)

• Workflow orchestration using config-first approaches (YAML/JSON definitions, step runners, etc.)

• Proven ability to drive technical vision, resolve ambiguity, and make architectural tradeoffs at scale.

• Strong background in distributed systems, task queues, asynchronous workflows, and backend performance optimization.

• Experience in cloud-native environments (AWS, GCP, or Azure), including containerization, monitoring, a