Lead Software Engineer - Agentic AI
Salary not listed • Plano, TX, United States • Full-time
Posted 1mo ago
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Job Location
Plano, TX, United States
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer within the Consumer and Community Banking - Deposits 2.0 team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Responsibilities
- Execute creative software solutions, design, development, and technical troubleshooting.
- Define and drive the platform roadmap for agent-based capabilities, focusing on measurable outcomes, reliability, and usability.
- Lead end-to-end delivery of core agent platform components, including software development kits, reference implementations, and integration patterns.
- Partner with product, engineering, risk, and control stakeholders to align requirements, prioritize trade-offs, and unblock execution.
- Establish quality, performance, and operational standards for agent workloads, including monitoring, testing, and incident readiness.
- Translate experimentation into production by driving clear architecture decisions, scalable designs, and repeatable deployment practices.
- Guide responsible development practices by embedding governance, privacy, and model risk considerations into platform design.
- Communicate technical strategy and progress to senior stakeholders with clarity, data, and pragmatic recommendations.
- Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
- Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Requirements
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- Proficiency in Python (primary for agent orchestration and LLM tooling) and/or TypeScript / Java / Go for enterprise backend integration.
- Design hybrid search pipelines (dense vector retrieval, BM25, rerankers) paired with vector databases like Pinecone, Milvus, Qdrant, or pgvector.
- Build scalable microservices using FastAPI, Spring Boot, or Node.js to expose agent interfaces (REST, WebSockets, Server-Sent Events for streaming tokens and tool calls).
- Demonstrated experience leading effective use of approved AI-assisted software development tools.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
- Production experience with multi-agent and workflow orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI, LlamaIndex Workflows, Semantic Kernel).
- Deep expertise in structuring model tool calls, JSON schema validation, dynamic API integration, sandboxed code execution, and MCP (Model Context Protocol).
- Implement short-term and episodic memory (scratchpads, state graphs, vector-based retrieval, conversational buffer compaction).
- Advanced prompt engineering, chain-of-thought, ReAct (Reasoning + Acting), reflection loops, and output grounding/guardrails.