AI (GenAI) Engineer

Ethereum Technologies LLC; Palo Alto (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Ethereum Technologies LLC is seeking an AI/ML engineer to design GenAI-powered tools for network troubleshooting, including triage assistants and KPI summaries. You will build RAG pipelines, embeddings, and grounding strategies, while productionizing prompts with CI/CD, automated tests, and monitoring.

The role requires strong Python/SQL, data engineering, and experience with Azure services. Collaborating with data engineering, security, and RAN SMEs, you will translate network issues into

Qualifications

• Strong Python and SQL skills for large-scale telemetry/time-series datasets.
• Experience delivering production-grade AI/ML engineering solutions.
• Strong background in data engineering and ML Ops practices.

Responsibilities

• Build, deploy, and operate GenAI-powered network troubleshooting tools with measurable impact.
• Design and implement RAG pipelines with grounding and citations.
• Industrialize CI/CD pipelines, tests, canaries, monitoring, and SLOs for AI services.

Skills

Python

SQL

Data engineering

Telemetry data

Education

BS/MS in Computer Science, Electrical Engineering, Data Science, or related field

Tools

Azure Functions

Azure DevOps

Git

LangChain/LlamaIndex

Job description

• Build, deploy, and operate GenAI-powered tools that accelerate network troubleshooting: triage assistants, KPI summaries, anomaly detection/explanations, and recommended next actions with citations to source data.
• Design and implement RAG pipelines: document preparation (chunking/metadata), embeddings, vector search with re-ranking, grounding and citation strategies, semantic caching, and safety guardrails.
• Ship reliable services: productionize models and prompts with CI/CD, automated tests, canary/A–B releases, monitoring/alerts, and SLOs for accuracy, grounding, latency, and cost.
• Implement evaluation and continuous monitoring: offline and online eval harnesses, golden sets, human-in-the-loop review, prompt/knowledge drift detection, and token/cost budgets.
• Integrate with internal systems and tools: alarms and KPI platforms, ticketing, inventory/topology APIs, runbooks, and dashboards to close the loop from detection to remediation.
• Collaborate cross-functionally with data engineering, platform/security, and RAN SMEs to take use cases from discovery to production and iterate based on measurable impact (e.g., MTTR reduction, accuracy lift, fewer escalations).

Working knowledge of GenAI development patterns, including:

• Retrieval-Augmented Generation (RAG): chunking strategies, embeddings, hybrid search, re-ranking, grounding with citations, vector stores (e.g., Azure AI Search)
• Prompt design: system prompts, few-shot patterns, structured outputs (JSON/JSON Schema), function/tool calling
• Evaluation fundamentals: response quality, grounding, accuracy, latency, cost, and safety
• Production mindset: robust logging/monitoring, tracing, observability, troubleshooting; security basics (RBAC, managed identities, Key Vault, data privacy/PII handling), and operational readiness (rate limits, retries, timeouts, backoff, caching).
• Solid understanding of 4G/5G RAN and mobility concepts (e.g., handovers, drops, throughput, congestion, interference, PRB utilization, RSRP/RSRQ/SINR).
• Ability to translate network issues into measurable KPIs and investigative workflows, producing actionable outputs for operations and engineering (e.g., RCA steps, remediation recommendations, and change validation plans).

Preferred qualifications

• Built an internal assistant/copilot for network operations, triage, or RCA using KPIs, alarms, tickets, and documentation; experience grounding outputs with traceable evidence and citations.
• Experience with agentic workflows and orchestration (function/tool calling, multi-step chains, retries/guardrails) to automate diagnosis and propose actions.
• MLOps/LLMOps practices: CI/CD for pipelines/services, model/prompt/knowledge-based versioning, automated evaluations (e.g., RAG quality), drift monitoring, observability (OpenTelemetry), and cost/token controls.
• Familiarity with GenAI frameworks and tooling (e.g., Semantic Kernel, Lang Chain/LlamaIndex), MLflow/Model Registry, vector databases, and prompt/unit regression testing.
• Understanding of telecom standards and tooling: 3GPP concepts, vendor-specific counters (e.g., Ericsson/Nokia/Samsung)
• Relevant Azure certification (or in progress), especially Azure AI Engineer Associate.
• BS/MS in computer science, Electrical Engineering, Data Science, or a related technical field; or equivalent practical experience.
• 3–5 years of experience in AI/ML engineering, data engineering, or applied data science delivering production-grade solutions.
• Strong Python and SQL skills; mastery working with large-scale telemetry/time-series datasets and building reliable, testable data transformations.
• Hands-on experience with Azure services for data/AI solutions, including:
• Azure Functions or similar serverless compute
• Azure DevOps (or similar CI/CD tooling), Git, and automated testing

ETHEREUM TECHNOLOGIES LLC is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. ETHEREUM TECHNOLOGIES LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will ETHEREUM TECHNOLOGIES LLC require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract