AlphaSense
Staff Site Reliability Engineer
Remote - United States · Staff+
Sponsorship not specified$150k-$225kDetected 28 days ago
PythonGoAWSGCPAzureCloud PlatformsPrometheusGrafanaDatadogDevOpsSite Reliability EngineeringIncident ResponseRecruitingTCP/IPDNSLoad BalancingResearchLeadershipCommunicationCollaborationMentoring
About the role
- Our Site Reliability Engineering team is growing, and we are looking for a highly experienced Staff Site Reliability Engineer to help shape the future of reliability, scalability, and performance at AlphaSense.
- Our mission is to engineer our platform to the reliability standards of mission-critical systems, targeting 99.99% uptime, while continuously enhancing our systems and processes.
- This role is key to that mission and goes beyond traditional system maintenance
Responsibilities
- Architect Reliability Paved Paths: Build frameworks and self-service tooling that let teams own the reliability of their services in a "You Build It, You Run It" culture.
- Lead AI-Driven Reliability: Drive our AIOps strategy - automating diagnostics, remediation, and proactive failure prevention.
- Champion Reliability Culture: Embed SRE practices across engineering via design reviews, production readiness, and operational standards.
- Incident Leadership: Act as Incident Commander during critical events, modeling operational excellence, and ensuring blameless postmortems lead to lasting improvements.
- Advance Observability: Deliver end-to-end monitoring, tracing, and profiling (Prometheus, Grafana, OTEL, Continuous Profiling) to optimize performance proactively.
- With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust.
Requirements
- 8+ years of experience in Site Reliability Engineering, DevOps, or a similar role, with at least 3+ of those years operating in a Senior+ SRE position
- Proficiency in at least one programming/scripting language (Python, Go, or similar).
- Experience with monitoring & alerting (Prometheus, Grafana, Datadog, ELK).
- Familiarity with advanced observability (OTEL, continuous profiling).
- Proven incident management experience, including leading high-severity incidents and postmortems.
Skills
- Hands-on expertise with cloud platforms (AWS, GCP, or Azure) and Kubernetes.
- Strong troubleshooting skills across the full stack.
- Excellent communication and collaboration skills.
Compensation
- AlphaSense is an equal-opportunity employer.
- We are committed to a work environment that supports, inspires, and respects all individuals.
- All employees share in the responsibility for fulfilling AlphaSense's commitment to equal employment opportunity.
- This policy applies to every aspect of employment at AlphaSense, including recruitment, hiring, training, advancement, and termination.
- Recruiting Scams and Fraud
- We at AlphaSense have been made aware of fraudulent job postings and individuals impersonating AlphaSense recruiters.
Benefits
- Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients' own research content.
Company info
- Embed SRE practices across engineering via design reviews, production readiness, and operational standards.
- You will act as a force multiplier, mentoring fellow engineers, influencing architectural decisions, and setting the technical bar for reliability across the company.
- Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500.
- Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland.
Equal opportunity
- In addition, it is the policy of AlphaSense to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations, and ordinances where a particular employee works.
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This listing is sourced directly from AlphaSense's careers page and normalized into a canonical job model.