Note: The job is a remote job and is open to candidates in USA. AHEAD builds platforms for digital business, focusing on digital transformation through cloud infrastructure and analytics. The Senior AI Engineer will develop and deploy multi-agent systems, integrate enterprise systems, and ensure the quality and reliability of AI solutions.
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
- Integrate LLMs, SLMs, embeddings, and retrieval pipelines (Pinecone, Elasticsearch, Snowflake Cortex, pgvector)
- Create and operate LLM/ML endpoints, agent memory/state stores, and event-driven triggers
- Implement reusable components that become part of AHEAD’s agent library and client solution accelerators
- Build real-time and batch workflows using Python, Kafka, EventBridge, Airflow, Snowflake, S3, n8n, AWS Batch, and similar tools
- Connect agents to enterprise systems (SharePoint, Salesforce, ServiceNow, Jira, Oracle, databases, APIs)
- Implement RAG, tool-calling, function calling, and structured output pipelines for production-ready agentic tasks
- Ensure robust data transformations, validation, and versioning for downstream agent workflows
- 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
- Participate in incident reviews, debugging multi-agent flows, and ensuring predictable performance
- Work closely with client stakeholders to understand use cases, pain points, and success criteria
- Translate business needs into technical agent designs and execution roadmaps
- Participate in agile ceremonies, demos, and working sessions with client teams
- Contribute to proposals, SOWs, architecture diagrams, and client documentation when needed
- Apply enterprise standards for data security, access control, auditing, model governance, and safe AI usage
- Embed monitoring, lineage, PII handling, and policy constraints into agentic flows
- Coach junior engineers on agent design patterns, RAG, orchestration, and clean engineering practices
- Contribute to internal best practices, reference architectures, and reusable components
- Support onboarding of new engineers and help scale AHEAD's agentic engineering community
Skills
- Strong Python engineering background, including async patterns, APIs, and event-driven design
- Hands-on experience with multi-agent frameworks (LangGraph, Autogen, CrewAI, LangChain, etc.)
- Demonstrated ability to build production ETL, orchestration, or workflow automation pipelines (Kafka, EventBridge, Airflow, Celery, n8n, AWS services)
- Experience with vector DBs and retrieval pipelines (Pinecone, pgvector, Elasticsearch, LlamaIndex)
- Familiarity with MLOps, observability, CI/CD, containerization, and model deployment patterns
- Strong documentation habits and comfort working in fast-paced agile environments
- 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
Benefits
- Medical, Dental, and Vision Insurance
- 401(k)
- Paid company holidays
- Paid time off
- Paid parental and caregiver leave
- Plus more! See benefits
Company Overview
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