Senior Software Engineer, AI (Contract)

Quick Facts

• Role: Senior Software Engineer, AI (Contractor)
• Focus: Agentic & AI engineering, production delivery, and developer productivity

Description

Design, build, and operate production-quality agentic applications using LLMs, including multi-agent orchestration, tool integration, and lifecycle hooks. Create MCP tool and resource interfaces for safe access to backend systems and enterprise data, and engineer prompts for reliable structured output with evaluation and context-management across long conversations and agent handoffs. Integrate agentic development into CI/CD and engineering workflows, prototype new capabilities with teams, and lead end-to-end delivery from implementation through monitoring.

Responsibilities

• Build agentic applications with multi-agent orchestration, subagent delegation, tool integration, and lifecycle hooks
• Design MCP tool and resource interfaces for safe, reliable data access
• Engineer prompts for structured output (JSON schemas), validation/retry loops, and evaluation frameworks
• Manage context across long documents, multi-turn conversations, and multi-agent handoffs; implement escalation and human-in-the-loop patterns
• Configure and extend Codex/Claude Code for team use (AGENTS.md/CLAUDE.md, custom commands, agent skills, rules, plan mode)
• Integrate agentic development into CI/CD for automated code review, test generation, and PR feedback with minimized false positives
• Build and maintain MCP server integrations (project- and user-scoped) across engineering workflows
• Prototype, validate, and deliver AI capabilities with engineering teams; own implementation, testing, deployment, monitoring, and iteration
• Provide hands-on technical leadership via architecture discussions, code reviews, troubleshooting, mentoring, and documentation

Requirements

• 6+ years of professional software engineering experience, including significant hands-on work with AI/LLM-powered or agentic applications
• Strong programming skills (Java, Python, Go, Rust, or C++) and solid engineering fundamentals (API design, testing, debugging, code review, maintainable code)
• Production-grade experience with agentic SDKs/harnesses, MCP, and LLMs (tool use, orchestration, RAG, context management, structured output, and evaluation)
• Experience designing MCP tool/resource interfaces and reasoning about tool selection, error handling, and reliability in multi-agent systems
• Demonstrated experience integrating AI into CI/CD and developer workflows
• Ability to work in ambiguous problem spaces and make pragmatic engineering decisions
• Strong written and verbal communication skills; experience mentoring and leading through influence
• Experience building an engineering knowledge base for agentic workflows (ingestion, organization, updates, retrieval) connected to agents via RAG and MCP with source citations

Benefits

• Contract role with ownership of the full AI/agentic delivery lifecycle and production systems responsibilities
• Opportunity to mentor engineers and contribute reusable agentic patterns, standards, and documentation