Staff Software Engineer

Shields Group; San Francisco (CA); Hybrid; USD 220,000 - 290,000; Full time

Benefits offered by this job

Equity

Job summary

Shields Group seeks a Senior/Staff Software Engineer for the Agentic Platform to build scalable agentic AI systems. You will own architecture, orchestration, memory, retrieval, and guardrails in a production context.

The role emphasizes learning from failed experiments and delivering reliable, enterprise-grade software. You will collaborate with product and engineering teams across SF and NYC, mentor peers, and drive architecture decisions while balancing rapid experimentation with system

Qualifications

• 4+ years of software engineering experience at senior-to-staff level.
• Hands-on experience building agentic systems.
• Experience with LLM orchestration and tool use.
• Experience with multi-agent reasoning and retrieval/contexts.
• Familiar with data-intensive distributed systems in enterprise environments.
• Strong observability, testing, and reliability practices.

Responsibilities

• Own the architecture for agentic systems, including orchestration, memory, retrieval, evaluation, and guardrails.
• Build and harden reasoning layers transforming input data into root-cause insights at enterprise scale.
• Establish evaluation and testing frameworks for non-deterministic systems.
• Partner with Engineering and Product to shape the technical vision and roadmap.
• Mentor engineers and raise engineering standards across the org.

Skills

4+ years of software engineering

agentic AI experience

LLM orchestration

Tool and function calling

Multi-step/multi-agent reasoning

Retrieval and context engineering

Interoperability protocols (MCP)

Non-deterministic system failures

Messy real-world data

Technical mentorship

Senior-to-staff experience

Enterprise domain experience

Education

N/A

Tools

MCP protocol

Job description

Senior/Staff Software Engineer, Agentic Platform

Compensation: $220,000–$290,000 Base Salary + Equity

Openings: 3

Focus Areas: LLMs | Agentic AI | Distributed Systems | Artificial Intelligence | System Design

About the Company

Shields Group Search is partnering with a rapidly growing, Series B-funded AI company that helps manufacturers reduce the cost of poor quality and improve product reliability.

The company's AI platform unifies siloed, messy operational data into a single, actionable root-cause picture, enabling manufacturers to identify quality issues, improve reliability, and reduce operational costs.

The company serves major global manufacturers across heavy equipment, industrial technology, and commercial vehicles, with three major enterprise customers signed within the last few months.

With no direct competitor currently operating in this category, the company recently closed a major Series B (~$65M+ raised to date) and plans to raise a Series C next year.

About the Role

We are seeking a Senior/Staff Software Engineer, Agentic Platform to help build and scale production-grade agentic AI systems.

This is a senior-to-staff-level individual contributor opportunity for an engineer who has successfully shipped agentic systems into production, understands their limitations, and can speak specifically about what they built, why they made certain technical decisions, and what failed along the way.

The role sits on the company's Agentic Platform team, which is expanding in San Francisco alongside an existing engineering organization in New York and a Product Manager based in San Francisco.

The central technical challenge is data: customer, service, field, telematics, warranty, and aftermarket signals that are disconnected, heterogeneous, and largely unstructured.

You’ll own the architecture and infrastructure needed to transform these inputs into reliable, agent-driven reasoning and actionable root-cause insights at enterprise scale.

The company values engineers with experience in both successful launches and unsuccessful experiments. Given how early the agentic AI field remains, understanding failed approaches and their underlying causes is considered just as valuable as shipping successful systems.

The engineering culture is fast-moving, high-accountability, direct, and low-ego. Feedback is given openly and acted upon quickly. Hard technical problems occasionally require weekend pushes, while the team also respects personal time off.

Ideal Candidate Profile

We’re looking for a senior or staff-level engineer who combines hands‑on agentic AI experience with a strong distributed systems foundation and enterprise engineering rigor.

Ideal backgrounds include engineering teams working on:

• Amazon Bedrock
• Meta AI
• Comparable enterprise-scale AI infrastructure and platform teams

The ideal candidate will have:

• Hands‑on production experience with LLM orchestration, tool use, multi‑agent reasoning, retrieval, and evaluation.
• Experience designing data‑intensive distributed systems in B2B or enterprise environments.
• Strong architectural opinions backed by real production experience.
• The ability to mentor and influence engineering teams without requiring formal authority.
• A demonstrated history of stable professional tenure rather than repeated six‑to‑nine‑month job changes.
• Experience balancing rapid experimentation and MVP delivery with production reliability.

Must‑Have Qualifications

• 4+ years of software engineering experience, with the technical maturity expected of a senior‑to‑staff‑level individual contributor.
• Recent, hands‑on experience building agentic systems, including:
• LLM orchestration
• Tool and function calling
• Multi‑step and multi‑agent reasoning
• Retrieval and context engineering
• Interoperability protocols such as MCP or comparable technologies
• Strong intuition for non‑deterministic system failures, including experience with the evaluation, testing, and observability practices required to make LLM‑driven systems reliable.
• Experience working with messy, heterogeneous real‑world data, transforming incomplete and unstructured information into formats that AI systems can reason over reliably.
• A demonstrated track record of technical mentorship, influencing and supporting other engineers without relying on formal managerial authority.
• Senior‑to‑staff‑level engineering experience, rather than an early‑career background.
• Meaningful enterprise domain experience, including an understanding of the architectural, scalability, and reliability requirements that distinguish enterprise software from consumer applications.

Key Responsibilities

1. Agentic Systems Architecture

Own the technical architecture for agentic systems, including orchestration, tool use, memory, retrieval, evaluation, observability, and guardrails designed for noisy and incomplete input data.

2. Reasoning Infrastructure & Distributed Systems

Build and harden the reasoning layer and supporting infrastructure that transforms customer data from ingestion through agent-driven reasoning into root‑cause insights with manufacturer‑scale reliability.

3. Evaluation, Testing & Reliability

Establish rigorous evaluation and testing frameworks for non‑deterministic systems.

Measure agent accuracy against expert‑validated ground truth and real customer outcomes, including detection rates, investigation speed, and warranty costs.

4. Technical Vision & Product Collaboration

Partner closely with Engineering and Product teams to shape the technical vision, architecture, and roadmap for the agent platform.

Raise engineering standards through thoughtful code reviews, design documentation, architectural guidance, and technical direction.

6. Technical Mentorship

Mentor engineers on agentic patterns and system design, unblock complex technical challenges, and share context and expertise across the organization.

What Makes a Strong Candidate

We’re particularly interested in engineers who demonstrate the following:

• Real production experience: You’ve shipped agentic systems into production and have meaningful lessons and production scars to share.
• Strong architectural opinions: You can explain how and why you built systems in a particular way, including the tradeoffs behind your decisions.
• Experience with failed experiments: You’ve encountered approaches that didn’t work and can articulate what went wrong and what you learned.
• Consistent professional tenure: Your career reflects meaningful ownership and sustained contributions rather than frequent job changes every six to nine months.
• Recent agentic AI experience: At least the past year of your engineering experience includes hands‑on agentic work, ideally with a production launch.
• Distributed systems expertise: You’ve designed and owned complex distributed systems, preferably in data‑intensive B2B SaaS environments.
• Data‑first mindset: You believe in a Data First philosophy and can make sound architectural decisions in ambiguous, rapidly evolving environments.
• Strong execution: You can move quickly, ship MVPs, and iterate without sacrificing the fundamentals of production‑grade engineering.

Profiles That May Not Be Aligned

• Candidates with repeated six‑to‑nine‑month job changes.
• Engineers who are still very early in their careers rather than operating at a senior or staff level.
• Candidates whose experience is exclusively in consumer applications, without exposure to enterprise‑scale engineering requirements.

Compensation & Logistics

• Additional Compensation: Equity
• Work Arrangement: Hybrid
• Open Positions: 3