Security Operations Engineer

About Alchemy

Alchemy is the Web3 infrastructure and developer platform that powers millions of users and the world’s most innovative blockchain applications. From enabling $1+ trillion in financial transactions worldwide to scaling L2s and enabling DeFi, Alchemy provides the infrastructure and tools developers need to build reliable, scalable, and accessible experiences.

Trusted by companies like JPMorgan, Stripe, Visa, Franklin Templeton, Nike, and backed by a16z, Coatue, Silver Lake, Lightspeed, and Stanford University, Alchemy is building the foundational layer for a decentralized and AI-enabled Web3 ecosystem. For more information, visit alchemy.com.

The Role

We're looking for a Security Operations Engineer to improve how Alchemy detects threats, investigates incidents, and reduces operational security risk. This is a hands-on individual-contributor role with no people-management responsibilities.

You'll investigate suspicious activity and build the systems that make the next investigation faster and more reliable. AI-assisted engineering and investigation should be part of your daily work: connecting evidence, developing detections, building response workflows, and checking the results against source data.

You'll also help the team get better at this work. Through shared tooling, code review, pairing, and practical documentation, you'll give teammates capabilities they can use independently.

What You Will Do

• Detect and investigate threats. Triage alerts, hunt for suspicious activity, and investigate across cloud infrastructure, corporate systems, identity, endpoints, and production environments. Establish what happened from evidence and communicate uncertainty clearly.

• Engineer detection coverage. Build and tune detections, onboard useful telemetry, and maintain reliable log pipelines. Test rules against representative attacks and benign activity; address missing coverage and noisy alerts.

• Respond to incidents. Participate in the security on-call rotation and incident response, including scoping, containment, recovery, and post-incident improvements. Preserve evidence and coordinate changes with system owners.

• Build AI-assisted security workflows. Automate evidence collection, alert enrichment, investigation timelines, and response preparation. Connect agents to approved tools and data sources so they can complete bounded tasks with traceable results.

• Verify before trusting. Evaluate AI-assisted workflows against known cases and adversarial inputs. Require evidence for conclusions, test false-positive and missed-threat behavior, and keep human approval for disruptive containment actions.

• Reduce operational exposure. Partner with Infrastructure and IT on vulnerability remediation, cloud and host hardening, identity controls, and attack-surface monitoring. Prioritize findings by exposure and impact, then verify remediation.

• Help secure agent operations. Work with platform and product-security partners on operational controls for agent identities, credentials, tool access, and audit logging. Investigate misuse and build detections for suspicious agent behavior.

• Improve how the team works. Share reusable code, investigation skills, runbooks, and evaluation cases. Pair with teammates, review automation, and teach approaches they can apply to their own investigations.

• Measure defensive outcomes. Track detection coverage, alert quality, investigation effort, response time, and remediation progress. Use those measures to decide what to improve next.

   

What We Are Looking For

• Hands-on security operations experience spanning detection engineering, threat hunting, and incident response.

• Strong scripting and software-building ability, especially Python; experience with APIs, version control, tests, and operating automation in production.

• Experience with a SIEM such as Panther, Splunk, or an equivalent platform, including detection logic and log analysis.

• Working knowledge of cloud security, identity, endpoint telemetry, networking, and Linux systems. Ability to investigate across system boundaries.

• Evidence of building and using AI-assisted tools in security or adjacent engineering work. You can show how you validate outputs, handle failures, and protect sensitive information.

• Sound incident judgment: you can separate a hypothesis from a finding, preserve evidence, and choose when to escalate or contain.

• A record of making teammates more effective through tools, mentoring, code review, or documentation, without needing management authority.

• Clear written communication and the willingness to own both urgent investigations and the follow-through that prevents repeat incidents.

Helpful Experience

• AWS, Kubernetes, bare-metal infrastructure, detection-as-code, or SOAR workflows.

• Digital forensics, threat intelligence, or testing detections through attack simulation.

• Securing AI agents and tool integrations, including prompt injection, credential misuse, and data-exfiltration risks.

• Blockchain infrastructure or other environments with sensitive keys and high-impact production systems.

   

What Success Looks Like

• Investigations reach evidence-backed conclusions faster. Detection coverage improves, repeat noise declines, and remediation is verified. The team adopts tools and workflows you've built, with clear limits on what agents may do and a tested path for handling failures.

   

Benefits & Perks

🏥 Private Health Insurance

💪 Gym Reimbursement

🚅 Commuter Benefits

🌴 Flexible Time Off

🥙 In-Office Group Meals

🧠 Learning & Development Stipend

🌎 Company Sponsored Conferences & Events

🎧 Books & Audiobook subscription with Bookster