Agentic Software Engineer (Full Stack)

Openkrill; United States; Remote; USD 150,000 - 230,000; Full time

Job summary

Specright is seeking an Agentic Software Engineer (Full-Stack) to ship reliable, user-facing AI agent products to production. You will own production systems end-to-end, from design to deployment, including chat-based interfaces and internal copilots.

You will work with TypeScript/Node.js or Python, focusing on agent evaluation, tracing, and observability. This is a 100% remote role in a fast-paced, collaborative environment.

Qualifications

• Shipped production software end-to-end, not just demos.
• Built or owned 1–2 agentic features or products in production.
• Deep understanding of agentic coding best practices and prompt hygiene.

Responsibilities

• Design, build, and deliver agentic products end-to-end.
• Use agentic coding tools daily to accelerate delivery.
• Architect agent internals: tool calls, memory, state, retrieval pipelines.

Skills

Full-stack engineering

LLM-powered agents

Agentic design principles

Agent evals & tracing

Reliability & testing

Tools

TypeScript/Node.js

Python

Job description

Specright is the first purpose-built, patented platform for Specification Management. Whether it's packaging, raw materials, formulas, products, or machines, Specright helps companies digitize, map, and take action across their supply chain to reduce costs, increase profitability, and drive sustainability. Specright serves customers across industries, including packaging, food and beverage, consumer packaged goods, pharmaceutical, retail, industrials, and more.

We'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 roleis 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 justprototypes 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.

We are an energetic company with an entrepreneurial, informal, versatile, intelligent, and fast-paced culture. We are a 100% remote company and promote an open and relatively flat organization with an emphasis on collaboration, sharing ideas, and information. It's more important to innovate than to worry about making mistakes.

Specright is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.