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Strong brand, mid-level generalist AI role, and metro location increase applicant competition.
Specialized agentic LLM, observability, and production ML skills limit cross-industry transferability.
Explicit 2–6 years plus mandatory ML, LLM, cloud, and observability skills make shortlisting highly selective.
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Design, build, and maintain agentic AI platform components including agents, tools, workflows, and system integrations.
Implement observability (tracing, logging, metrics) and safety guardrails across the AI lifecycle to monitor quality, cost, and reliability.
Lead experimentation with prompts, models, and workflows; translate business needs into AI solutions collaborating with cross-functional teams.
2-6 years of experience in software engineering, data engineering, ML engineering, data science, or MLOps-related roles.
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or equivalent practical experience.
Strong programming skills in Python or equivalent languages.
Experience with cloud platforms (AWS/Azure/GCP), containers/serverless, observability tools (OpenTelemetry, Prometheus, Grafana, ELK), and strong SQL plus data frameworks (Pandas/Spark/dbt).
Experienced working with LLM/Generative AI fundamentals including prompting, embeddings, vector search, RAG, and agentic AI patterns.
Comfortable owning end-to-end stack: data pipelines, AI agent logic, infrastructure, and production monitoring.
Able to lead observability-first engineering, implement safety controls, and collaborate effectively with product, data, security, and compliance teams.