The RoleWe're looking for an Agentic Software Engineer (Full-Stack) to help us ship reliable, user-facing AI
agent products to production - fast. You'll work at the intersection of modern AI tooling and strong
software engineering discipline, building agentic experiences that our customers and internal teams rely
on every day.
This is not a research role. You will own production systems end-to-end: designing agent architectures,
writing and reviewing code (often with agentic coding assistants), setting up rigorous evals, and operating
what you build. If you care about making AI agents that actually work - not just demo well - this role
is for you.
What You'll Do- Build and Ship Agentic Applications Design, develop, and deliver agentic products end-to-end -
including chat-based interfaces, AI workflow tools, and internal copilots - that serve real users in
production. - Leverage Agentic Coding Workflows Use modern agentic coding tools daily (e.g., Claude Code, Codex,
Cursor, and similar assistants) to accelerate delivery while maintaining high code quality and engineering
standards. - Design Agent Systems Architect agent internals: tool calling, multi-step orchestration, memory and state management, retrieval pipelines, permissions models, and failure recovery strategies.
- Own Evals and Quality Build and maintain agent evaluation infrastructure - regression suites, scenario-based tests, golden traces, and both offline and online metrics - so you always know whether your agent got better or worse.
- Implement Observability Instrument agents with production-grade observability: distributed tracing, prompt and version tracking, tool-call telemetry, and cost/latency monitoring.
- Own Production Readiness Take responsibility for the full lifecycle: rollout plans, QA, guardrails, incident response, and continuous improvement of deployed agents.
What You Bring (Must-Haves)- Proven full-stack engineering ability. You've shipped production software end-to-end - not just prototypes or demos.
- Hands-on experience building LLM-powered agents that work in production. You've owned at
least 1-2 agentic features or products through deployment and operation. - Deep familiarity with agentic coding best practices. You understand task decomposition, agent
delegation, prompt hygiene, iterative loops, and how to review and steer agentic outputs effectively. - Practical experience with agent evals and tracing. You've gone beyond model benchmarking to
build evaluation systems specifically for agent behavior - including trace-based debugging and
regression detection. - Solid engineering fundamentals. Testing, debugging, security basics, performance optimization,
and reliability are second nature to you.
Nice-to-Haves- Proficiency in TypeScript/Node.js and/or Python, with experience in modern web stacks and
startup-pace delivery. - Familiarity with agent tooling ecosystems: prompt/version stores, eval harnesses, tracing and
telemetry platforms (OpenTelemetry, LangSmith, Datadog, Honeycomb, or similar). - Experience with RAG architectures: vector databases, indexing strategies, chunking approaches,
and retrieval evaluation. - Experience designing tool APIs for agents: structured output schemas, idempotency, rate limiting,
and error handling patterns that make agents more reliable.
Why Specright- Entrepreneurial culture. We're fast-paced, informal, and flat - collaboration and innovation matter more than hierarchy or fear of mistakes.
- Real impact. Your work will power AI capabilities that touch real supply chain decisions across major industries.
- Autonomy and ownership. We hire senior people and trust them to make decisions, ship fast, and continuously improve what they build.
- Global team. You'll collaborate across time zones with talented colleagues who care about craft.
- Competitive perks. Competitive salaries, flexible work hours, and a full benefits package (Medical, Vision, and Dental).
