Senior AI Engineer

About the role

We are looking for an Agentic AI Engineer to design and build AI agents that continuously analyze ServiceNow Discovery logs, classify failures, perform root cause analysis, and recommend or generate corrective actions at enterprise scale across millions of infrastructure targets. You will develop agentic observability capabilities for MID Servers and Discovery schedules, integrate LLM APIs including OpenAI and Anthropic using RAG and vector databases, and convert operational runbooks into reusable agentic workflows using advanced Python engineering. Strong infrastructure troubleshooting and network protocol knowledge is required alongside production-grade Python and CI/CD experience.

What you will do

• Design and build AI agents that continuously analyze Discovery logs, execution results, errors, and failed discoveries at scale.
• Develop agents capable of classifying and correlating failures, performing troubleshooting, identifying probable root causes, and recommending corrective actions.
• Build capabilities for agents to analyze and recommend or generate corrections to ServiceNow Discovery probes and patterns, with appropriate testing, guardrails, and human approval before production changes.
• Convert operational knowledge, runbooks, and recurring troubleshooting procedures into reusable agentic workflows, progressively reducing manual investigation and improving Discovery reliability.
• Design and build AI agents that continuously assess the health of the ServiceNow Discovery ecosystem, including MID Servers, discovery schedules/playbooks, target execution, throughput, latency, failures, retries, and discovery coverage.
• Develop agents that regularly collect, aggregate, and interpret metrics and telemetry from ServiceNow Discovery, MID Servers, logs, monitoring platforms, and other relevant data sources.

Must haves

• Advanced Python development experience of at least 4+ years and REST API design capabilities, including building APIs, data-processing pipelines, integrations, automation, and production-grade engineering solutions.
• Strong experience with modern software development and SDLC practices and toolchains, including Git/GitHub, Jenkins or equivalent CI/CD platforms, artifact repositories, automated testing, code quality/security scanning, release management, and deployment automation.
• Practical experience integrating GenAI APIs into software applications, such as OpenAI and Anthropic, and working knowledge of Retrieval-Augmented Generation (RAG) and vector databases.
• Practical knowledge of infrastructure engineering with Linux, Windows Server, compute, virtualization/cloud infrastructure, authentication, processes/services, and infrastructure troubleshooting.
• Working knowledge of TCP/IP, DNS, routing, firewalls, ports, SSH, WMI/WinRM, SNMP, HTTP/S, and common network and infrastructure troubleshooting techniques.
• Experience with high-volume logs, metrics, errors, and operational datasets to identify patterns, anomalies, trends, and root causes and turn them into actionable engineering improvements.
• Upper-Intermediate English level.

Nice to haves

• Hands-on experience with ServiceNow Discovery, including MID Servers, Discovery Patterns/Probes, credentials, schedules, Discovery Status, ECC Queue, and troubleshooting Discovery failures.
• Experience developing or modifying ServiceNow Discovery Patterns and Probes and understanding how infrastructure attributes and relationships are discovered.
• Experience with ServiceNow CMDB/CSDM, Configuration Items (CIs), identification/reconciliation, relationships, and CMDB data quality.
• Experience with observability technologies such as Prometheus, OpenTelemetry, and Grafana.

Benefits

Professional growth

• Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.

Competitive compensation

• Competitive USD-based compensation and budgets for education, fitness, and team activities.

A selection of exciting projects

• Join projects with modern solutions development and top-tier clients, including Fortune 500 enterprises and leading product brands.

Flextime

• Tailor your schedule for an optimal work-life balance with options to work from home or from the office.

Recruitment process

Asynchronous stage – An automated, self-paced track that helps move faster and provide quicker feedback:

• Short online form to confirm basic requirements.
• 30–60 minute skills assessment.
• 5-minute introduction video.

Synchronous stage – Live interviews:

• Technical interview with the engineering team.
• Final interview with future teammates.
• If it is a match, you will receive an offer.