Jobs and Careers

Senior AI Engineer, AI Services

United States, United Statesfull_timeVerifiedPosted 2 Jun 2026

About the role

AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation.

At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD.

We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived.

We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.

Key Responsibilities

Solution Development & Deployment
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

Enterprise Integration & Workflow Automation
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.

Quality, Observability & Reliability
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.

Client Collaboration & Delivery Excellence
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.

Security, Governance & Compliance
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.

Mentorship & Internal Development
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.

Qualifications

Required
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.

Preferred
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.