Forward Deployed Engineer

Astral Insights LLC; Raleigh (NC); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Equity

Health benefits

Access to advanced AI tooling

Job summary

Astral Insights LLC is seeking a Forward Deployed Engineer to play a crucial role in client engagements. You will configure AI agents, design data pipelines, and present findings to executives. Ideal candidates will have 2-5 years of engineering experience, proficiency in SQL and Python, and a desire to innovate in an AI-focused environment. The position offers a base salary of $120,000 to $150,000, equity, and health benefits, with opportunities for significant exposure to strategic decisions in a growing team.

Qualifications

• 2 to 5 years of engineering experience, ideally in data engineering, full-stack development, or AI/ML work.
• Experience with SQL, Python, data modeling, and AWS is required.
• Experience in manufacturing or supply chain domains is a plus.

Responsibilities

• Configure Artemis agents for client deployments and ensure data quality.
• Design and implement data layers that feed Artemis agents.
• Present findings to VPs and directors, building ROI narratives.
• Travel to client sites for meetings and implementation.

Skills

SQL

Python

Data modeling

Client-facing communication

Prompt engineering

Tools

AWS

Microsoft Azure

Job description

Astral Insights is a B2B AI company building Artemis, an operational intelligence platform for manufacturing, quality, and supply chain teams. Artemis is headless in nature and integrates with experience layers like Microsoft Teams and our web app, deploying AI agents inside our clients' operations to detect signals, diagnose root causes, and drive actions that ultimately improve the bottom line. We serve enterprise clients across life sciences, specialized manufacturing, and healthcare organizations. We operate as a lean, senior team and we hire people who want to own outcomes, not tickets.

The Role

The Forward Deployed Engineer (FDE) is our tip of the spear inside client engagements. You sit between our clients' data, our Artemis platform, and the executives who signed the deal. You configure Artemis agents to the client's domain, wire up the data pipelines that feed them, stand up the full-stack surfaces clients interact with, and you stand in front of VPs and directors to show the work and the ROI.

This role is built for someone who embraces modern AI-supported development, tried and true SWE fundamentals, and client-facing implementation. You do not need to be the world's best data engineer, full-stack developer, prompt engineer, or implementation consultant. You need to be capable across all of these domains and passionate about working closely with clients to solve meaningful problems. If the idea of being thrown a problem you have never solved before and shipping it in a week sounds exciting instead of terrifying, this might be a fit.

What You'll Do

Configure Artemis agents for clients

Own the end-to-end configuration of agents on the Artemis platform for each client deployment. Prompt engineering, context engineering, tool wiring, evaluation loops, and tuning until the agent behaves the way the client's operators expect.

Build and own the client data layer

Design and ship the bronze, silver, and gold layers that feed Artemis. Ingest messy enterprise data (ERP extracts, SQL Server, flat files, APIs), clean it, model it, and land it in the structures our agents consume. You are responsible for data quality, not just data movement.

Ship full-stack features end to end

Run working sessions with client data, IT, and operations teams. Translate their requirements into sprint work. Handle the ambiguity directly rather than punting it back to the founders.

Present to executives and make the business case

Walk VPs and directors through what the agents found, what actions were taken, and what it was worth. Build and deliver ROI narratives. Our champions have to be able to defend the investment to their leadership, and your deliverables are what they use.

Travel to client sites when it matters

Be on the ground for kickoffs, major checkpoints, executive readouts, and go-lives. Expect roughly a dozen travel days per year across the united states.

Close the signal-to-action loop

Own the outcome, not a subtask. If a signal is firing wrong, if a dashboard is stale, if an agent is hallucinating, if the data pipeline broke, it is your problem to diagnose and fix, regardless of which layer it lives in.

Use AI tools creatively and responsibly

Use Claude Code, Codex, and similar tools as force multipliers. Know when to trust the output, when to verify it, and when to throw it out. We expect you to ship more than a traditional engineer, not the same amount with more help.

Who You Are

2 to 5 years of engineering experience

Across some combination of data engineering, full-stack development, and AI or ML work. You do not need depth in all three, but you need to have shipped production systems in at least one and be hungry to learn the others fast.

Comfortable with SQL, Python, data modeling, and the bronze / silver / gold medallion pattern (or equivalent lakehouse / warehouse patterns). Hands-on experience with AWS is required (our primary stack), and experience with Microsoft Azure is a plus since we integrate with it as well.

Real prompt and context engineering chops

Full-stack range

Client-facing presence

You have led calls with client teams. You have presented to executives. You can translate a technical result into a business outcome and a dollar amount without being prompted. You are comfortable being the face of the company on a customer call.

AI-native operator

You use Claude Code, Codex, Cursor, or similar tools every day and have opinions about them. You see AI tools as the way to punch above your weight, not a crutch. You are excited about walking into problems you cannot yet solve and solving them anyway.

Comfort with ambiguity

Early-stage startup energy. Things break. Scope changes. Clients ask for things that were not in the SOW. You handle it and keep the trains moving.

Nice to Have

• Experience in manufacturing, quality, or supply chain domains (root cause analysis, CAPA, quality investigations, S&OP, logistics).
• Experience with Microsoft Fabric, Power BI, or the broader Microsoft data stack (we integrate with Azure).
• Experience with Teams bot development, Microsoft Graph, or Microsoft Bot Framework.
• Experience building with Anthropic, OpenAI, or AWS Bedrock model APIs at production scale.
• Prior forward-deployed, solutions engineering, or implementation engineering experience at a B2B SaaS or AI company.
• Bilingual (English / Spanish) is a plus given our distributed team.

What We Offer

• Base salary of $120,000 to $150,000 depending on experience, plus meaningful equity and health benefits.
• Joining a growing team that is winning enterprise logos and redefining AI use for decision making.
• Direct exposure to the founding team (CEO, COO, CTO) and the strategic decisions that shape the company.
• The full Artemis platform as your canvas. If you see something that should be built differently, build it.
• Heavy investment in AI tooling. If a tool makes you faster, we buy it.

How to Apply

Ready to ship?

Send a short note explaining what you have shipped recently, a specific example of an AI or agent system you built, and why this role fits you now. Links to code, writeups, or product demos are welcome in place of a resume.