Ahead
Senior AI Engineer, AI Services
United States · Senior
Sponsorship not specified$200k-$250kDetected 229 days ago
PythonElasticsearchSnowflakeDatabricksVector DatabasesAWSCloud PlatformsCI/CDKafkaMachine LearningAirflowData AnalysisData EngineeringLLMsRAGAgentic AIMLOpsLangGraphAgileJiraSalesforceAuditingCadenceTest Automation
About the role
- We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.
- This OTE range may vary based on the candidate's relevant experience, qualifications, and geographic location.
- Why AHEAD: Through our daily work and internal groups like Moving Women AHEAD and RISE AHEAD, we value and benefit from diversity of people, ideas, experience, and everything in between.
Responsibilities
- Build and deploy multi-agent systems using frameworks such as LangChain, LangGraph, Autogen, CrewAI, and LlamaIndex.
- Develop custom agents for document processing, workflow automation, SDLC acceleration, data analysis, and business process orchestration.
- Create and operate LLM/ML endpoints, agent memory/state stores, and event-driven triggers.
- Build real-time and batch workflows using Python, Kafka, EventBridge, Airflow, Snowflake, S3, n8n, AWS Batch, and similar tools.
- Implement RAG, tool-calling, function calling, and structured output pipelines for production-ready agentic tasks.
- Implement monitoring, metrics, and guardrails for multi-agent systems (timeouts, retries, constraints, circuit breakers).
- Build automated testing for agent behaviors, prompts, ETL/batch jobs, and model outputs.
- Translate business needs into technical agent designs and execution roadmaps.
- Coach junior engineers on agent design patterns, RAG, orchestration, and clean engineering practices.
- Support onboarding of new engineers and help scale AHEAD's agentic engineering community.
Requirements
- Hands-on experience with multi-agent frameworks (LangGraph, Autogen, CrewAI, LangChain, etc.).
- Experience with vector DBs and retrieval pipelines (Pinecone, pgvector, Elasticsearch, LlamaIndex).
- Familiarity with MLOps, observability, CI/CD, containerization, and model deployment patterns.
- Experience integrating with enterprise systems or APIs in production.
- Experience with Snowflake Cortex, Databricks Mosaic, NVIDIA NIMs, or similar AI platform components.
- Experience operating agentic systems at scale, including safety constraints and system-level debugging.
- Experience in consulting, client-facing engineering, or co-development models.
- Visible growth of AHEAD's reputation for agentic AI expertise.
- Required
- Strong Python engineering background, including async patterns, APIs, and event-driven design.
- Demonstrated ability to build production ETL, orchestration, or workflow automation pipelines (Kafka, EventBridge, Airflow, Celery, n8n, AWS services).
- Strong documentation habits and comfort working in fast-paced agile environments.
- Preferred
- Success Metrics & Environment
- Delivery of reliable, scalable agentic solutions that measurably improve client outcomes.
Skills
- Final hiring decisions are ultimately made by humans.
- Candidates will not be penalized for choosing to opt-out.
Compensation
- The compensation range indicated in this posting reflects the On-Target Earnings ("OTE") for this role, which includes a base salary and any applicable target bonus amount.
Visa & Work Authorization
- You may opt-out of the review or analysis of your application and resume by AI tools by using the General Application.
This listing is sourced directly from Ahead's careers page and normalized into a canonical job model.